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doi:10.15139/S3/EKDFDL | Data for: Caregiver social support and child toilet training in rural Odisha, India: what types of support facilitate training and how? | <|begin_of_text|><|start_header_id|>system<|end_header_id|> You are a research archivist expert in dataset metadata. Answer the question truthfully. <|eot_id|><|start_header_id|>user<|end_header_id|> Here is the Description of a dataset. Description:'De-identified data for 'Sclar, G.D. & Mosler, H-J. Caregiver social support and child toilet training in rural Odisha, India: what types of support facilitate training and how? Applied Psychology: Health and Well-being.' This cross-sectional study examined the role of social support in child toilet training using mediation and conditional process analyses. The dataset includes survey responses from caregivers of children <5 years old living in Ganjam and Gajapati districts in Odisha, India. Data was collected between December 2019 - February 2020' . Please return only a json list of at most 3 Keywords corresponding to the Description:.<|eot_id|><|start_header_id|>assistant<|end_header_id|> {"Answer" : ["perceived stress","self-efficacy","social support","toilet training"]} <|eot_id|> | Here is the Description of a dataset. Description:'De-identified data for 'Sclar, G.D. & Mosler, H-J. Caregiver social support and child toilet training in rural Odisha, India: what types of support facilitate training and how? Applied Psychology: Health and Well-being.' This cross-sectional study examined the role of social support in child toilet training using mediation and conditional process analyses. The dataset includes survey responses from caregivers of children <5 years old living in Ganjam and Gajapati districts in Odisha, India. Data was collected between December 2019 - February 2020' . Please return only a json list of at most 3 Keywords corresponding to the Description:. | De-identified data for 'Sclar, G.D. & Mosler, H-J. Caregiver social support and child toilet training in rural Odisha, India: what types of support facilitate training and how? Applied Psychology: Health and Well-being.' This cross-sectional study examined the role of social support in child toilet training using mediation and conditional process analyses. The dataset includes survey responses from caregivers of children <5 years old living in Ganjam and Gajapati districts in Odisha, India. Data was collected between December 2019 - February 2020 | Social Sciences | perceived stress; self-efficacy; social support; toilet training |
doi:10.15139/S3/FIKOH4 | Data for RICHS Placental lncRNA expression associated with placental cadmium concentrations and birth weight | <|begin_of_text|><|start_header_id|>system<|end_header_id|> You are a research archivist expert in dataset metadata. Answer the question truthfully. <|eot_id|><|start_header_id|>user<|end_header_id|> Here is the Description of a dataset. Description:'Background: Prenatal heavy metal exposures, such as cadmium, can have negative effects on infant birth weight – among other developmental outcomes – with placental dysfunction potentially playing a role in these effects. In this study, we examined how differential placental expression of long non-coding RNAs (lncRNAs) may be associated with cadmium exposure and whether differences in the expression of those lncRNAs was associated with fetal growth.Methods: In the Rhode Island Child Health Study (RICHS) we used data from whole transcriptome RNA sequencing (n=199) to examine the association between lncRNA expression and measures of infant birth weight as well as placental cadmium concentrations' . Please return only a json list of at most 3 Keywords corresponding to the Description:.<|eot_id|><|start_header_id|>assistant<|end_header_id|> {"Answer" : ["birth weight","cadmium","RNA"]} <|eot_id|> | Here is the Description of a dataset. Description:'Background: Prenatal heavy metal exposures, such as cadmium, can have negative effects on infant birth weight – among other developmental outcomes – with placental dysfunction potentially playing a role in these effects. In this study, we examined how differential placental expression of long non-coding RNAs (lncRNAs) may be associated with cadmium exposure and whether differences in the expression of those lncRNAs was associated with fetal growth.Methods: In the Rhode Island Child Health Study (RICHS) we used data from whole transcriptome RNA sequencing (n=199) to examine the association between lncRNA expression and measures of infant birth weight as well as placental cadmium concentrations' . Please return only a json list of at most 3 Keywords corresponding to the Description:. | Background: Prenatal heavy metal exposures, such as cadmium, can have negative effects on infant birth weight – among other developmental outcomes – with placental dysfunction potentially playing a role in these effects. In this study, we examined how differential placental expression of long non-coding RNAs (lncRNAs) may be associated with cadmium exposure and whether differences in the expression of those lncRNAs was associated with fetal growth.Methods: In the Rhode Island Child Health Study (RICHS) we used data from whole transcriptome RNA sequencing (n=199) to examine the association between lncRNA expression and measures of infant birth weight as well as placental cadmium concentrations | Medicine, Health and Life Sciences | birth weight; cadmium; RNA |
doi:10.15139/S3/FUC5EW | Data for Placental microRNA Expression Associates with Birthweight through Control of Adipokines: Results from Two Independent Cohorts | <|begin_of_text|><|start_header_id|>system<|end_header_id|> You are a research archivist expert in dataset metadata. Answer the question truthfully. <|eot_id|><|start_header_id|>user<|end_header_id|> Here is the Description of a dataset. Description:'MicroRNAs are non-coding RNAs that regulate gene expression post-transcriptionally. In the placenta, the master regulator of fetal growth and development, microRNAs shape the basic processes of trophoblast biology and specific microRNA have been associated with fetal growth. To comprehensively assess the role of microRNAs in placental function and fetal development, we have performed small RNA sequencing to profile placental microRNAs from two independent mother-infant cohorts: the Rhode Island Child Health Study (n=225) and the New Hampshire Birth Cohort Study (n=317). We modeled microRNA counts on infant birthweight percentile (BWP) in each cohort, while accounting for race, sex, parity and technical factors, using negative binomial generalized linear models' . Please return only a json list of at most 3 Keywords corresponding to the Description:.<|eot_id|><|start_header_id|>assistant<|end_header_id|> {"Answer" : ["birthweight","microRNA"]} <|eot_id|> | Here is the Description of a dataset. Description:'MicroRNAs are non-coding RNAs that regulate gene expression post-transcriptionally. In the placenta, the master regulator of fetal growth and development, microRNAs shape the basic processes of trophoblast biology and specific microRNA have been associated with fetal growth. To comprehensively assess the role of microRNAs in placental function and fetal development, we have performed small RNA sequencing to profile placental microRNAs from two independent mother-infant cohorts: the Rhode Island Child Health Study (n=225) and the New Hampshire Birth Cohort Study (n=317). We modeled microRNA counts on infant birthweight percentile (BWP) in each cohort, while accounting for race, sex, parity and technical factors, using negative binomial generalized linear models' . Please return only a json list of at most 3 Keywords corresponding to the Description:. | MicroRNAs are non-coding RNAs that regulate gene expression post-transcriptionally. In the placenta, the master regulator of fetal growth and development, microRNAs shape the basic processes of trophoblast biology and specific microRNA have been associated with fetal growth. To comprehensively assess the role of microRNAs in placental function and fetal development, we have performed small RNA sequencing to profile placental microRNAs from two independent mother-infant cohorts: the Rhode Island Child Health Study (n=225) and the New Hampshire Birth Cohort Study (n=317). We modeled microRNA counts on infant birthweight percentile (BWP) in each cohort, while accounting for race, sex, parity and technical factors, using negative binomial generalized linear models | Medicine, Health and Life Sciences | birthweight; microRNA |
doi:10.15139/S3/GKH2QD | CHAMPS De-identified Dataset, v4.2 | <|begin_of_text|><|start_header_id|>system<|end_header_id|> You are a research archivist expert in dataset metadata. Answer the question truthfully. <|eot_id|><|start_header_id|>user<|end_header_id|> Here is the Description of a dataset. Description:'(rev. 2021-04-01) Request dataset here: https://champshealth.org/data-access/ Version 4.2 of the standard, de-identified CHAMPS dataset included these files: case demographics (including MITS measurements), verbal autopsy, DeCoDe results, TAC results, and lab results. One new column (site_iso_code) was added to this dataset to the file CHAMPS_deid_basic_demographics.csv. This dataset is updated monthly. The version of this dataset changes quarterly when a revised ICD-10 mapping document is uploaded.</br' . Please return only a json list of at most 3 Keywords corresponding to the Description:.<|eot_id|><|start_header_id|>assistant<|end_header_id|> {"Answer" : ["Anemias","Assays: Bordatella spp., C. difficile, C. diphtheria, H. influenzae, Arenavirus/Lassa Fever, MERS coronavirus, Salmonella spp., V. cholerae, Acinetobacter baumannii, Adenovirus, Adenovirus 40/41, Aeromonas spp., Ascaris lumbricoides, Astrovirus, Bartonella spp.","Bordetella parapertussi, Bordetella bronchiseptica","Bordetella pertussis, Bordetella holmseii","Bordetella pertussis (pertussis toxin), Brucellaspp., Burkholderia pseudomallei, C. difficile paLOC, C. difficile tcdA, C. difficile tcdB, Campylobacter coli, Campylobacter jejuni, Candida albicans, Crimean-Congo Hemorrhagic Fever virus (CCHF), Chikungunya virus, Chlamydia pneumoniae, Chlamydia trachomatis, Corynebacterium diptheriae","Corynebacterium ulcerans, Corynebacterium pseudotuberculosis","Corynebactrium spp. (tox gene), Coxiella burnettii","Cryptococcus neoformans, Cryptococcus gattii","Cryptosporidium parvum, Cytomegalovirus (CMV), Dengue (pan), Entamoeba histolytica, Escherichia coli (aaiC gene), Escherichia coli (aatA gene), Enterococcus facium, Enterococcus faecalis, Enterovirus, Escherichia coli (bfpA gene), Escherichia coli (eae gene), Escherichia coli/Shigella, Escherichia coli (heat-labile enterotoxin), Escherichia coli (heat-stable enterotoxin)","Bacterial Infections and Mycoses","Birth Trauma","Cancer","Cardiovascular Diseases","Cervical Insufficiency and Pelvic Anomalies","Cesarean Delivery","Chemically-Induced Disorders","Chorioamnionitis and Membrane Complications","Congenital Birth Defects","Congenital, Hereditary, and Neonatal Diseases and Abnormalities","Congenital Infection","Diarrheal Diseases","Digestive System Diseases","Disorders of Environmental Origin","Endocrine System Diseases","Epilepsy","Eye Diseases","Female Urogenital Diseases and Pregnancy Complications","Giardia spp, Group A Streptococcus, Group B Streptococcus, Haemophilus influenzae, Haemophilus influenzae type B, Human coronavirus 1 (229E), Human coronavirus 2 (NL63), Human coronavirus 3 (OC43), Human coronavirus 4 (HKU1), Hepatitis E virus, Human metapneumovirus (HMPV), Herpes simplex virus 1 (HSV1), Herpes simplex virus 2 (HSV2), Human nucleic acid control (Rnase P), Influenza A, Influenza B, Internal Positive Control (IPC), Japanese encephalitis virus, Klebsiella pneumoniae","PAN Lassa Fever Virus, can cross react with other arenavirus","Lassa Fever Virus target 1 and target 2, Leptospira (pan-serovar), Listeria monocytogenes, Measles, MERS coronavirus (N gene), MERS coronavirus (upE gene), Moraxella catarrhalis, Mumps, MS2 phage for extraction control, Mycobacterium tuberculosis, Mycoplasma pneumoniae, Neisseria gonorrhoeae, Neisseria meningitidis, Nipah virus, Norovirus GI, Norovirus GII, Orientia tsutsugamushi, Parechovirus, Parvovirus B19 VP2","Parainfluenza virus type 1, type 2, type 3 and type 4","Plasmodium falciparum, Plasmodium vivax, Pneumocystis jirovecii, Pseudomonas aeruginosa, Respiratory syncytical virus (RSV), Rhinovirus, Rickettsia spp., Rift Valley Fever, Rotavirus A, Rotavirus B, Rotavirus C","Global Health","Heart Diseases","Hemic and Lymphatic Diseases","HIV","Immune System Diseases","Injury","Kidney Disease","Liver Disease","Lower Respiratory Infections","Malaria","Malnutrition","Malpresentation Before Labor","Maternal Circulatory and Respiratory Diseases","Maternal Diabetes","Maternal HIV","Maternal Hypertension","Maternal Infection","Maternal Injury and Accident","Maternal Medication or Toxic Exposure","Maternal Nutritional Disorder","Maternal Surgical and Medical Procedures","Measles","Meningitis/Encephalitis","Motor Neuron Disease","Multiple Gestation","Musculoskeletal Diseases","Neonatal Aspiration Syndromes","Neonatal Encephalopathy","Neonatal Preterm Birth Complications","Neonatal Sepsis","Neoplasms","Nervous System Diseases","Nutritional and Metabolic Diseases","Obstructed Labor and Fetal Malpresentation","Other Disorders of Fluid, Electrolyte and Acid-Base Balance","Other Endocrine, Metabolic, Blood and Immune Disorders","Other Gastrointestinal Disease","Other Immunodeficiencies","Other Infections","Other Injury","Other Labor and Delivery Complications","Other Maternal Factor","Other Neonatal Disorders","Other Neurological Disorders","Other Nutritional Deficiencies","Other Respiratory Diseases","Other Skin and Subcutaneous Diseases","Paralytic Ileus and Intestinal Obstruction","Parasitic Diseases","Pathological Conditions, Signs and Symptoms","Perinatal Asphyxia/Hypoxia","Placental Complications","Poisoning","Premature Rupture of Membranes","Preterm Labor or Delivery","Prolapsed Cord","Public Health","Respiratory Tract Diseases","Road Injuries","Sepsis","Sickle Cell Disorders","Skin and Connective Tissue Diseases","Spontaneous Abortion","Stomatognathic Diseases","Sudden Infant Death Syndrome (SIDS)","Syphilis","Tuberculosis (TB)","Umbilical Cord Complications","Upper Respiratory Infections","Uterine Fluid Disorders","Uterine Rupture","Virus Diseases","Wounds and Injuries"]} <|eot_id|> | Here is the Description of a dataset. Description:'(rev. 2021-04-01) Request dataset here: https://champshealth.org/data-access/ Version 4.2 of the standard, de-identified CHAMPS dataset included these files: case demographics (including MITS measurements), verbal autopsy, DeCoDe results, TAC results, and lab results. One new column (site_iso_code) was added to this dataset to the file CHAMPS_deid_basic_demographics.csv. This dataset is updated monthly. The version of this dataset changes quarterly when a revised ICD-10 mapping document is uploaded.</br' . Please return only a json list of at most 3 Keywords corresponding to the Description:. | (rev. 2021-04-01) Request dataset here: https://champshealth.org/data-access/ Version 4.2 of the standard, de-identified CHAMPS dataset included these files: case demographics (including MITS measurements), verbal autopsy, DeCoDe results, TAC results, and lab results. One new column (site_iso_code) was added to this dataset to the file CHAMPS_deid_basic_demographics.csv. This dataset is updated monthly. The version of this dataset changes quarterly when a revised ICD-10 mapping document is uploaded.</br | Medicine, Health and Life Sciences | Anemias; Assays: Bordatella spp., C. difficile, C. diphtheria, H. influenzae, Arenavirus/Lassa Fever, MERS coronavirus, Salmonella spp., V. cholerae, Acinetobacter baumannii, Adenovirus, Adenovirus 40/41, Aeromonas spp., Ascaris lumbricoides, Astrovirus, Bartonella spp.; Bordetella parapertussi, Bordetella bronchiseptica; Bordetella pertussis, Bordetella holmseii; Bordetella pertussis (pertussis toxin), Brucellaspp., Burkholderia pseudomallei, C. difficile paLOC, C. difficile tcdA, C. difficile tcdB, Campylobacter coli, Campylobacter jejuni, Candida albicans, Crimean-Congo Hemorrhagic Fever virus (CCHF), Chikungunya virus, Chlamydia pneumoniae, Chlamydia trachomatis, Corynebacterium diptheriae; Corynebacterium ulcerans, Corynebacterium pseudotuberculosis; Corynebactrium spp. (tox gene), Coxiella burnettii; Cryptococcus neoformans, Cryptococcus gattii; Cryptosporidium parvum, Cytomegalovirus (CMV), Dengue (pan), Entamoeba histolytica, Escherichia coli (aaiC gene), Escherichia coli (aatA gene), Enterococcus facium, Enterococcus faecalis, Enterovirus, Escherichia coli (bfpA gene), Escherichia coli (eae gene), Escherichia coli/Shigella, Escherichia coli (heat-labile enterotoxin), Escherichia coli (heat-stable enterotoxin); Bacterial Infections and Mycoses; Birth Trauma; Cancer; Cardiovascular Diseases; Cervical Insufficiency and Pelvic Anomalies; Cesarean Delivery; Chemically-Induced Disorders; Chorioamnionitis and Membrane Complications; Congenital Birth Defects; Congenital, Hereditary, and Neonatal Diseases and Abnormalities; Congenital Infection; Diarrheal Diseases; Digestive System Diseases; Disorders of Environmental Origin; Endocrine System Diseases; Epilepsy; Eye Diseases; Female Urogenital Diseases and Pregnancy Complications; Giardia spp, Group A Streptococcus, Group B Streptococcus, Haemophilus influenzae, Haemophilus influenzae type B, Human coronavirus 1 (229E), Human coronavirus 2 (NL63), Human coronavirus 3 (OC43), Human coronavirus 4 (HKU1), Hepatitis E virus, Human metapneumovirus (HMPV), Herpes simplex virus 1 (HSV1), Herpes simplex virus 2 (HSV2), Human nucleic acid control (Rnase P), Influenza A, Influenza B, Internal Positive Control (IPC), Japanese encephalitis virus, Klebsiella pneumoniae; PAN Lassa Fever Virus, can cross react with other arenavirus; Lassa Fever Virus target 1 and target 2, Leptospira (pan-serovar), Listeria monocytogenes, Measles, MERS coronavirus (N gene), MERS coronavirus (upE gene), Moraxella catarrhalis, Mumps, MS2 phage for extraction control, Mycobacterium tuberculosis, Mycoplasma pneumoniae, Neisseria gonorrhoeae, Neisseria meningitidis, Nipah virus, Norovirus GI, Norovirus GII, Orientia tsutsugamushi, Parechovirus, Parvovirus B19 VP2; Parainfluenza virus type 1, type 2, type 3 and type 4; Plasmodium falciparum, Plasmodium vivax, Pneumocystis jirovecii, Pseudomonas aeruginosa, Respiratory syncytical virus (RSV), Rhinovirus, Rickettsia spp., Rift Valley Fever, Rotavirus A, Rotavirus B, Rotavirus C; Global Health; Heart Diseases; Hemic and Lymphatic Diseases; HIV; Immune System Diseases; Injury; Kidney Disease; Liver Disease; Lower Respiratory Infections; Malaria; Malnutrition; Malpresentation Before Labor; Maternal Circulatory and Respiratory Diseases; Maternal Diabetes; Maternal HIV; Maternal Hypertension; Maternal Infection; Maternal Injury and Accident; Maternal Medication or Toxic Exposure; Maternal Nutritional Disorder; Maternal Surgical and Medical Procedures; Measles; Meningitis/Encephalitis; Motor Neuron Disease; Multiple Gestation; Musculoskeletal Diseases; Neonatal Aspiration Syndromes; Neonatal Encephalopathy; Neonatal Preterm Birth Complications; Neonatal Sepsis; Neoplasms; Nervous System Diseases; Nutritional and Metabolic Diseases; Obstructed Labor and Fetal Malpresentation; Other Disorders of Fluid, Electrolyte and Acid-Base Balance; Other Endocrine, Metabolic, Blood and Immune Disorders; Other Gastrointestinal Disease; Other Immunodeficiencies; Other Infections; Other Injury; Other Labor and Delivery Complications; Other Maternal Factor; Other Neonatal Disorders; Other Neurological Disorders; Other Nutritional Deficiencies; Other Respiratory Diseases; Other Skin and Subcutaneous Diseases; Paralytic Ileus and Intestinal Obstruction; Parasitic Diseases; Pathological Conditions, Signs and Symptoms; Perinatal Asphyxia/Hypoxia; Placental Complications; Poisoning; Premature Rupture of Membranes; Preterm Labor or Delivery; Prolapsed Cord; Public Health; Respiratory Tract Diseases; Road Injuries; Sepsis; Sickle Cell Disorders; Skin and Connective Tissue Diseases; Spontaneous Abortion; Stomatognathic Diseases; Sudden Infant Death Syndrome (SIDS); Syphilis; Tuberculosis (TB); Umbilical Cord Complications; Upper Respiratory Infections; Uterine Fluid Disorders; Uterine Rupture; Virus Diseases; Wounds and Injuries |
doi:10.15139/S3/GKH2QD | CHAMPS De-identified Dataset, v4.2 | <|begin_of_text|><|start_header_id|>system<|end_header_id|> You are a research archivist expert in dataset metadata. Answer the question truthfully. <|eot_id|><|start_header_id|>user<|end_header_id|> Here is the Description of a dataset. Description:'(rev. 2021-04-01) Request dataset here: https://champshealth.org/data-access/ Version 4.2 of the standard, de-identified CHAMPS dataset included these files: case demographics (including MITS measurements), verbal autopsy, DeCoDe results, TAC results, and lab results. One new column (site_iso_code) was added to this dataset to the file CHAMPS_deid_basic_demographics.csv. This dataset is updated monthly. The version of this dataset changes quarterly when a revised ICD-10 mapping document is uploaded.</br' . Please return only a json list of at most 3 Keywords corresponding to the Description:.<|eot_id|><|start_header_id|>assistant<|end_header_id|> {"Answer" : ["Anemias","Assays: Bordatella spp., C. difficile, C. diphtheria, H. influenzae, Arenavirus/Lassa Fever, MERS coronavirus, Salmonella spp., V. cholerae, Acinetobacter baumannii, Adenovirus, Adenovirus 40/41, Aeromonas spp., Ascaris lumbricoides, Astrovirus, Bartonella spp.","Bordetella parapertussi, Bordetella bronchiseptica","Bordetella pertussis, Bordetella holmseii","Bordetella pertussis (pertussis toxin), Brucellaspp., Burkholderia pseudomallei, C. difficile paLOC, C. difficile tcdA, C. difficile tcdB, Campylobacter coli, Campylobacter jejuni, Candida albicans, Crimean-Congo Hemorrhagic Fever virus (CCHF), Chikungunya virus, Chlamydia pneumoniae, Chlamydia trachomatis, Corynebacterium diptheriae","Corynebacterium ulcerans, Corynebacterium pseudotuberculosis","Corynebactrium spp. (tox gene), Coxiella burnettii","Cryptococcus neoformans, Cryptococcus gattii","Cryptosporidium parvum, Cytomegalovirus (CMV), Dengue (pan), Entamoeba histolytica, Escherichia coli (aaiC gene), Escherichia coli (aatA gene), Enterococcus facium, Enterococcus faecalis, Enterovirus, Escherichia coli (bfpA gene), Escherichia coli (eae gene), Escherichia coli/Shigella, Escherichia coli (heat-labile enterotoxin), Escherichia coli (heat-stable enterotoxin)","Bacterial Infections and Mycoses","Birth Trauma","Cancer","Cardiovascular Diseases","Cervical Insufficiency and Pelvic Anomalies","Cesarean Delivery","Chemically-Induced Disorders","Chorioamnionitis and Membrane Complications","Congenital Birth Defects","Congenital, Hereditary, and Neonatal Diseases and Abnormalities","Congenital Infection","Diarrheal Diseases","Digestive System Diseases","Disorders of Environmental Origin","Endocrine System Diseases","Epilepsy","Eye Diseases","Female Urogenital Diseases and Pregnancy Complications","Giardia spp, Group A Streptococcus, Group B Streptococcus, Haemophilus influenzae, Haemophilus influenzae type B, Human coronavirus 1 (229E), Human coronavirus 2 (NL63), Human coronavirus 3 (OC43), Human coronavirus 4 (HKU1), Hepatitis E virus, Human metapneumovirus (HMPV), Herpes simplex virus 1 (HSV1), Herpes simplex virus 2 (HSV2), Human nucleic acid control (Rnase P), Influenza A, Influenza B, Internal Positive Control (IPC), Japanese encephalitis virus, Klebsiella pneumoniae","PAN Lassa Fever Virus, can cross react with other arenavirus","Lassa Fever Virus target 1 and target 2, Leptospira (pan-serovar), Listeria monocytogenes, Measles, MERS coronavirus (N gene), MERS coronavirus (upE gene), Moraxella catarrhalis, Mumps, MS2 phage for extraction control, Mycobacterium tuberculosis, Mycoplasma pneumoniae, Neisseria gonorrhoeae, Neisseria meningitidis, Nipah virus, Norovirus GI, Norovirus GII, Orientia tsutsugamushi, Parechovirus, Parvovirus B19 VP2","Parainfluenza virus type 1, type 2, type 3 and type 4","Plasmodium falciparum, Plasmodium vivax, Pneumocystis jirovecii, Pseudomonas aeruginosa, Respiratory syncytical virus (RSV), Rhinovirus, Rickettsia spp., Rift Valley Fever, Rotavirus A, Rotavirus B, Rotavirus C","Global Health","Heart Diseases","Hemic and Lymphatic Diseases","HIV","Immune System Diseases","Injury","Kidney Disease","Liver Disease","Lower Respiratory Infections","Malaria","Malnutrition","Malpresentation Before Labor","Maternal Circulatory and Respiratory Diseases","Maternal Diabetes","Maternal HIV","Maternal Hypertension","Maternal Infection","Maternal Injury and Accident","Maternal Medication or Toxic Exposure","Maternal Nutritional Disorder","Maternal Surgical and Medical Procedures","Measles","Meningitis/Encephalitis","Motor Neuron Disease","Multiple Gestation","Musculoskeletal Diseases","Neonatal Aspiration Syndromes","Neonatal Encephalopathy","Neonatal Preterm Birth Complications","Neonatal Sepsis","Neoplasms","Nervous System Diseases","Nutritional and Metabolic Diseases","Obstructed Labor and Fetal Malpresentation","Other Disorders of Fluid, Electrolyte and Acid-Base Balance","Other Endocrine, Metabolic, Blood and Immune Disorders","Other Gastrointestinal Disease","Other Immunodeficiencies","Other Infections","Other Injury","Other Labor and Delivery Complications","Other Maternal Factor","Other Neonatal Disorders","Other Neurological Disorders","Other Nutritional Deficiencies","Other Respiratory Diseases","Other Skin and Subcutaneous Diseases","Paralytic Ileus and Intestinal Obstruction","Parasitic Diseases","Pathological Conditions, Signs and Symptoms","Perinatal Asphyxia/Hypoxia","Placental Complications","Poisoning","Premature Rupture of Membranes","Preterm Labor or Delivery","Prolapsed Cord","Public Health","Respiratory Tract Diseases","Road Injuries","Sepsis","Sickle Cell Disorders","Skin and Connective Tissue Diseases","Spontaneous Abortion","Stomatognathic Diseases","Sudden Infant Death Syndrome (SIDS)","Syphilis","Tuberculosis (TB)","Umbilical Cord Complications","Upper Respiratory Infections","Uterine Fluid Disorders","Uterine Rupture","Virus Diseases","Wounds and Injuries"]} <|eot_id|> | Here is the Description of a dataset. Description:'(rev. 2021-04-01) Request dataset here: https://champshealth.org/data-access/ Version 4.2 of the standard, de-identified CHAMPS dataset included these files: case demographics (including MITS measurements), verbal autopsy, DeCoDe results, TAC results, and lab results. One new column (site_iso_code) was added to this dataset to the file CHAMPS_deid_basic_demographics.csv. This dataset is updated monthly. The version of this dataset changes quarterly when a revised ICD-10 mapping document is uploaded.</br' . Please return only a json list of at most 3 Keywords corresponding to the Description:. | (rev. 2021-04-01) Request dataset here: https://champshealth.org/data-access/ Version 4.2 of the standard, de-identified CHAMPS dataset included these files: case demographics (including MITS measurements), verbal autopsy, DeCoDe results, TAC results, and lab results. One new column (site_iso_code) was added to this dataset to the file CHAMPS_deid_basic_demographics.csv. This dataset is updated monthly. The version of this dataset changes quarterly when a revised ICD-10 mapping document is uploaded.</br | Other | Anemias; Assays: Bordatella spp., C. difficile, C. diphtheria, H. influenzae, Arenavirus/Lassa Fever, MERS coronavirus, Salmonella spp., V. cholerae, Acinetobacter baumannii, Adenovirus, Adenovirus 40/41, Aeromonas spp., Ascaris lumbricoides, Astrovirus, Bartonella spp.; Bordetella parapertussi, Bordetella bronchiseptica; Bordetella pertussis, Bordetella holmseii; Bordetella pertussis (pertussis toxin), Brucellaspp., Burkholderia pseudomallei, C. difficile paLOC, C. difficile tcdA, C. difficile tcdB, Campylobacter coli, Campylobacter jejuni, Candida albicans, Crimean-Congo Hemorrhagic Fever virus (CCHF), Chikungunya virus, Chlamydia pneumoniae, Chlamydia trachomatis, Corynebacterium diptheriae; Corynebacterium ulcerans, Corynebacterium pseudotuberculosis; Corynebactrium spp. (tox gene), Coxiella burnettii; Cryptococcus neoformans, Cryptococcus gattii; Cryptosporidium parvum, Cytomegalovirus (CMV), Dengue (pan), Entamoeba histolytica, Escherichia coli (aaiC gene), Escherichia coli (aatA gene), Enterococcus facium, Enterococcus faecalis, Enterovirus, Escherichia coli (bfpA gene), Escherichia coli (eae gene), Escherichia coli/Shigella, Escherichia coli (heat-labile enterotoxin), Escherichia coli (heat-stable enterotoxin); Bacterial Infections and Mycoses; Birth Trauma; Cancer; Cardiovascular Diseases; Cervical Insufficiency and Pelvic Anomalies; Cesarean Delivery; Chemically-Induced Disorders; Chorioamnionitis and Membrane Complications; Congenital Birth Defects; Congenital, Hereditary, and Neonatal Diseases and Abnormalities; Congenital Infection; Diarrheal Diseases; Digestive System Diseases; Disorders of Environmental Origin; Endocrine System Diseases; Epilepsy; Eye Diseases; Female Urogenital Diseases and Pregnancy Complications; Giardia spp, Group A Streptococcus, Group B Streptococcus, Haemophilus influenzae, Haemophilus influenzae type B, Human coronavirus 1 (229E), Human coronavirus 2 (NL63), Human coronavirus 3 (OC43), Human coronavirus 4 (HKU1), Hepatitis E virus, Human metapneumovirus (HMPV), Herpes simplex virus 1 (HSV1), Herpes simplex virus 2 (HSV2), Human nucleic acid control (Rnase P), Influenza A, Influenza B, Internal Positive Control (IPC), Japanese encephalitis virus, Klebsiella pneumoniae; PAN Lassa Fever Virus, can cross react with other arenavirus; Lassa Fever Virus target 1 and target 2, Leptospira (pan-serovar), Listeria monocytogenes, Measles, MERS coronavirus (N gene), MERS coronavirus (upE gene), Moraxella catarrhalis, Mumps, MS2 phage for extraction control, Mycobacterium tuberculosis, Mycoplasma pneumoniae, Neisseria gonorrhoeae, Neisseria meningitidis, Nipah virus, Norovirus GI, Norovirus GII, Orientia tsutsugamushi, Parechovirus, Parvovirus B19 VP2; Parainfluenza virus type 1, type 2, type 3 and type 4; Plasmodium falciparum, Plasmodium vivax, Pneumocystis jirovecii, Pseudomonas aeruginosa, Respiratory syncytical virus (RSV), Rhinovirus, Rickettsia spp., Rift Valley Fever, Rotavirus A, Rotavirus B, Rotavirus C; Global Health; Heart Diseases; Hemic and Lymphatic Diseases; HIV; Immune System Diseases; Injury; Kidney Disease; Liver Disease; Lower Respiratory Infections; Malaria; Malnutrition; Malpresentation Before Labor; Maternal Circulatory and Respiratory Diseases; Maternal Diabetes; Maternal HIV; Maternal Hypertension; Maternal Infection; Maternal Injury and Accident; Maternal Medication or Toxic Exposure; Maternal Nutritional Disorder; Maternal Surgical and Medical Procedures; Measles; Meningitis/Encephalitis; Motor Neuron Disease; Multiple Gestation; Musculoskeletal Diseases; Neonatal Aspiration Syndromes; Neonatal Encephalopathy; Neonatal Preterm Birth Complications; Neonatal Sepsis; Neoplasms; Nervous System Diseases; Nutritional and Metabolic Diseases; Obstructed Labor and Fetal Malpresentation; Other Disorders of Fluid, Electrolyte and Acid-Base Balance; Other Endocrine, Metabolic, Blood and Immune Disorders; Other Gastrointestinal Disease; Other Immunodeficiencies; Other Infections; Other Injury; Other Labor and Delivery Complications; Other Maternal Factor; Other Neonatal Disorders; Other Neurological Disorders; Other Nutritional Deficiencies; Other Respiratory Diseases; Other Skin and Subcutaneous Diseases; Paralytic Ileus and Intestinal Obstruction; Parasitic Diseases; Pathological Conditions, Signs and Symptoms; Perinatal Asphyxia/Hypoxia; Placental Complications; Poisoning; Premature Rupture of Membranes; Preterm Labor or Delivery; Prolapsed Cord; Public Health; Respiratory Tract Diseases; Road Injuries; Sepsis; Sickle Cell Disorders; Skin and Connective Tissue Diseases; Spontaneous Abortion; Stomatognathic Diseases; Sudden Infant Death Syndrome (SIDS); Syphilis; Tuberculosis (TB); Umbilical Cord Complications; Upper Respiratory Infections; Uterine Fluid Disorders; Uterine Rupture; Virus Diseases; Wounds and Injuries |
doi:10.15139/S3/GKH2QD | CHAMPS De-identified Dataset, v4.2 | <|begin_of_text|><|start_header_id|>system<|end_header_id|> You are a research archivist expert in dataset metadata. Answer the question truthfully. <|eot_id|><|start_header_id|>user<|end_header_id|> Here is the Description of a dataset. Description:'(rev. 2021-04-01) Request dataset here: https://champshealth.org/data-access/ Version 4.2 of the standard, de-identified CHAMPS dataset included these files: case demographics (including MITS measurements), verbal autopsy, DeCoDe results, TAC results, and lab results. One new column (site_iso_code) was added to this dataset to the file CHAMPS_deid_basic_demographics.csv. This dataset is updated monthly. The version of this dataset changes quarterly when a revised ICD-10 mapping document is uploaded.</br' . Please return only a json list of at most 3 Keywords corresponding to the Description:.<|eot_id|><|start_header_id|>assistant<|end_header_id|> {"Answer" : ["Anemias","Assays: Bordatella spp., C. difficile, C. diphtheria, H. influenzae, Arenavirus/Lassa Fever, MERS coronavirus, Salmonella spp., V. cholerae, Acinetobacter baumannii, Adenovirus, Adenovirus 40/41, Aeromonas spp., Ascaris lumbricoides, Astrovirus, Bartonella spp.","Bordetella parapertussi, Bordetella bronchiseptica","Bordetella pertussis, Bordetella holmseii","Bordetella pertussis (pertussis toxin), Brucellaspp., Burkholderia pseudomallei, C. difficile paLOC, C. difficile tcdA, C. difficile tcdB, Campylobacter coli, Campylobacter jejuni, Candida albicans, Crimean-Congo Hemorrhagic Fever virus (CCHF), Chikungunya virus, Chlamydia pneumoniae, Chlamydia trachomatis, Corynebacterium diptheriae","Corynebacterium ulcerans, Corynebacterium pseudotuberculosis","Corynebactrium spp. (tox gene), Coxiella burnettii","Cryptococcus neoformans, Cryptococcus gattii","Cryptosporidium parvum, Cytomegalovirus (CMV), Dengue (pan), Entamoeba histolytica, Escherichia coli (aaiC gene), Escherichia coli (aatA gene), Enterococcus facium, Enterococcus faecalis, Enterovirus, Escherichia coli (bfpA gene), Escherichia coli (eae gene), Escherichia coli/Shigella, Escherichia coli (heat-labile enterotoxin), Escherichia coli (heat-stable enterotoxin)","Bacterial Infections and Mycoses","Birth Trauma","Cancer","Cardiovascular Diseases","Cervical Insufficiency and Pelvic Anomalies","Cesarean Delivery","Chemically-Induced Disorders","Chorioamnionitis and Membrane Complications","Congenital Birth Defects","Congenital, Hereditary, and Neonatal Diseases and Abnormalities","Congenital Infection","Diarrheal Diseases","Digestive System Diseases","Disorders of Environmental Origin","Endocrine System Diseases","Epilepsy","Eye Diseases","Female Urogenital Diseases and Pregnancy Complications","Giardia spp, Group A Streptococcus, Group B Streptococcus, Haemophilus influenzae, Haemophilus influenzae type B, Human coronavirus 1 (229E), Human coronavirus 2 (NL63), Human coronavirus 3 (OC43), Human coronavirus 4 (HKU1), Hepatitis E virus, Human metapneumovirus (HMPV), Herpes simplex virus 1 (HSV1), Herpes simplex virus 2 (HSV2), Human nucleic acid control (Rnase P), Influenza A, Influenza B, Internal Positive Control (IPC), Japanese encephalitis virus, Klebsiella pneumoniae","PAN Lassa Fever Virus, can cross react with other arenavirus","Lassa Fever Virus target 1 and target 2, Leptospira (pan-serovar), Listeria monocytogenes, Measles, MERS coronavirus (N gene), MERS coronavirus (upE gene), Moraxella catarrhalis, Mumps, MS2 phage for extraction control, Mycobacterium tuberculosis, Mycoplasma pneumoniae, Neisseria gonorrhoeae, Neisseria meningitidis, Nipah virus, Norovirus GI, Norovirus GII, Orientia tsutsugamushi, Parechovirus, Parvovirus B19 VP2","Parainfluenza virus type 1, type 2, type 3 and type 4","Plasmodium falciparum, Plasmodium vivax, Pneumocystis jirovecii, Pseudomonas aeruginosa, Respiratory syncytical virus (RSV), Rhinovirus, Rickettsia spp., Rift Valley Fever, Rotavirus A, Rotavirus B, Rotavirus C","Global Health","Heart Diseases","Hemic and Lymphatic Diseases","HIV","Immune System Diseases","Injury","Kidney Disease","Liver Disease","Lower Respiratory Infections","Malaria","Malnutrition","Malpresentation Before Labor","Maternal Circulatory and Respiratory Diseases","Maternal Diabetes","Maternal HIV","Maternal Hypertension","Maternal Infection","Maternal Injury and Accident","Maternal Medication or Toxic Exposure","Maternal Nutritional Disorder","Maternal Surgical and Medical Procedures","Measles","Meningitis/Encephalitis","Motor Neuron Disease","Multiple Gestation","Musculoskeletal Diseases","Neonatal Aspiration Syndromes","Neonatal Encephalopathy","Neonatal Preterm Birth Complications","Neonatal Sepsis","Neoplasms","Nervous System Diseases","Nutritional and Metabolic Diseases","Obstructed Labor and Fetal Malpresentation","Other Disorders of Fluid, Electrolyte and Acid-Base Balance","Other Endocrine, Metabolic, Blood and Immune Disorders","Other Gastrointestinal Disease","Other Immunodeficiencies","Other Infections","Other Injury","Other Labor and Delivery Complications","Other Maternal Factor","Other Neonatal Disorders","Other Neurological Disorders","Other Nutritional Deficiencies","Other Respiratory Diseases","Other Skin and Subcutaneous Diseases","Paralytic Ileus and Intestinal Obstruction","Parasitic Diseases","Pathological Conditions, Signs and Symptoms","Perinatal Asphyxia/Hypoxia","Placental Complications","Poisoning","Premature Rupture of Membranes","Preterm Labor or Delivery","Prolapsed Cord","Public Health","Respiratory Tract Diseases","Road Injuries","Sepsis","Sickle Cell Disorders","Skin and Connective Tissue Diseases","Spontaneous Abortion","Stomatognathic Diseases","Sudden Infant Death Syndrome (SIDS)","Syphilis","Tuberculosis (TB)","Umbilical Cord Complications","Upper Respiratory Infections","Uterine Fluid Disorders","Uterine Rupture","Virus Diseases","Wounds and Injuries"]} <|eot_id|> | Here is the Description of a dataset. Description:'(rev. 2021-04-01) Request dataset here: https://champshealth.org/data-access/ Version 4.2 of the standard, de-identified CHAMPS dataset included these files: case demographics (including MITS measurements), verbal autopsy, DeCoDe results, TAC results, and lab results. One new column (site_iso_code) was added to this dataset to the file CHAMPS_deid_basic_demographics.csv. This dataset is updated monthly. The version of this dataset changes quarterly when a revised ICD-10 mapping document is uploaded.</br' . Please return only a json list of at most 3 Keywords corresponding to the Description:. | (rev. 2021-04-01) Request dataset here: https://champshealth.org/data-access/ Version 4.2 of the standard, de-identified CHAMPS dataset included these files: case demographics (including MITS measurements), verbal autopsy, DeCoDe results, TAC results, and lab results. One new column (site_iso_code) was added to this dataset to the file CHAMPS_deid_basic_demographics.csv. This dataset is updated monthly. The version of this dataset changes quarterly when a revised ICD-10 mapping document is uploaded.</br | Social Sciences | Anemias; Assays: Bordatella spp., C. difficile, C. diphtheria, H. influenzae, Arenavirus/Lassa Fever, MERS coronavirus, Salmonella spp., V. cholerae, Acinetobacter baumannii, Adenovirus, Adenovirus 40/41, Aeromonas spp., Ascaris lumbricoides, Astrovirus, Bartonella spp.; Bordetella parapertussi, Bordetella bronchiseptica; Bordetella pertussis, Bordetella holmseii; Bordetella pertussis (pertussis toxin), Brucellaspp., Burkholderia pseudomallei, C. difficile paLOC, C. difficile tcdA, C. difficile tcdB, Campylobacter coli, Campylobacter jejuni, Candida albicans, Crimean-Congo Hemorrhagic Fever virus (CCHF), Chikungunya virus, Chlamydia pneumoniae, Chlamydia trachomatis, Corynebacterium diptheriae; Corynebacterium ulcerans, Corynebacterium pseudotuberculosis; Corynebactrium spp. (tox gene), Coxiella burnettii; Cryptococcus neoformans, Cryptococcus gattii; Cryptosporidium parvum, Cytomegalovirus (CMV), Dengue (pan), Entamoeba histolytica, Escherichia coli (aaiC gene), Escherichia coli (aatA gene), Enterococcus facium, Enterococcus faecalis, Enterovirus, Escherichia coli (bfpA gene), Escherichia coli (eae gene), Escherichia coli/Shigella, Escherichia coli (heat-labile enterotoxin), Escherichia coli (heat-stable enterotoxin); Bacterial Infections and Mycoses; Birth Trauma; Cancer; Cardiovascular Diseases; Cervical Insufficiency and Pelvic Anomalies; Cesarean Delivery; Chemically-Induced Disorders; Chorioamnionitis and Membrane Complications; Congenital Birth Defects; Congenital, Hereditary, and Neonatal Diseases and Abnormalities; Congenital Infection; Diarrheal Diseases; Digestive System Diseases; Disorders of Environmental Origin; Endocrine System Diseases; Epilepsy; Eye Diseases; Female Urogenital Diseases and Pregnancy Complications; Giardia spp, Group A Streptococcus, Group B Streptococcus, Haemophilus influenzae, Haemophilus influenzae type B, Human coronavirus 1 (229E), Human coronavirus 2 (NL63), Human coronavirus 3 (OC43), Human coronavirus 4 (HKU1), Hepatitis E virus, Human metapneumovirus (HMPV), Herpes simplex virus 1 (HSV1), Herpes simplex virus 2 (HSV2), Human nucleic acid control (Rnase P), Influenza A, Influenza B, Internal Positive Control (IPC), Japanese encephalitis virus, Klebsiella pneumoniae; PAN Lassa Fever Virus, can cross react with other arenavirus; Lassa Fever Virus target 1 and target 2, Leptospira (pan-serovar), Listeria monocytogenes, Measles, MERS coronavirus (N gene), MERS coronavirus (upE gene), Moraxella catarrhalis, Mumps, MS2 phage for extraction control, Mycobacterium tuberculosis, Mycoplasma pneumoniae, Neisseria gonorrhoeae, Neisseria meningitidis, Nipah virus, Norovirus GI, Norovirus GII, Orientia tsutsugamushi, Parechovirus, Parvovirus B19 VP2; Parainfluenza virus type 1, type 2, type 3 and type 4; Plasmodium falciparum, Plasmodium vivax, Pneumocystis jirovecii, Pseudomonas aeruginosa, Respiratory syncytical virus (RSV), Rhinovirus, Rickettsia spp., Rift Valley Fever, Rotavirus A, Rotavirus B, Rotavirus C; Global Health; Heart Diseases; Hemic and Lymphatic Diseases; HIV; Immune System Diseases; Injury; Kidney Disease; Liver Disease; Lower Respiratory Infections; Malaria; Malnutrition; Malpresentation Before Labor; Maternal Circulatory and Respiratory Diseases; Maternal Diabetes; Maternal HIV; Maternal Hypertension; Maternal Infection; Maternal Injury and Accident; Maternal Medication or Toxic Exposure; Maternal Nutritional Disorder; Maternal Surgical and Medical Procedures; Measles; Meningitis/Encephalitis; Motor Neuron Disease; Multiple Gestation; Musculoskeletal Diseases; Neonatal Aspiration Syndromes; Neonatal Encephalopathy; Neonatal Preterm Birth Complications; Neonatal Sepsis; Neoplasms; Nervous System Diseases; Nutritional and Metabolic Diseases; Obstructed Labor and Fetal Malpresentation; Other Disorders of Fluid, Electrolyte and Acid-Base Balance; Other Endocrine, Metabolic, Blood and Immune Disorders; Other Gastrointestinal Disease; Other Immunodeficiencies; Other Infections; Other Injury; Other Labor and Delivery Complications; Other Maternal Factor; Other Neonatal Disorders; Other Neurological Disorders; Other Nutritional Deficiencies; Other Respiratory Diseases; Other Skin and Subcutaneous Diseases; Paralytic Ileus and Intestinal Obstruction; Parasitic Diseases; Pathological Conditions, Signs and Symptoms; Perinatal Asphyxia/Hypoxia; Placental Complications; Poisoning; Premature Rupture of Membranes; Preterm Labor or Delivery; Prolapsed Cord; Public Health; Respiratory Tract Diseases; Road Injuries; Sepsis; Sickle Cell Disorders; Skin and Connective Tissue Diseases; Spontaneous Abortion; Stomatognathic Diseases; Sudden Infant Death Syndrome (SIDS); Syphilis; Tuberculosis (TB); Umbilical Cord Complications; Upper Respiratory Infections; Uterine Fluid Disorders; Uterine Rupture; Virus Diseases; Wounds and Injuries |
doi:10.15139/S3/GTCNT3 | Dorothea Dix Hospital Records Collection, 1856-1919 | <|begin_of_text|><|start_header_id|>system<|end_header_id|> You are a research archivist expert in dataset metadata. Answer the question truthfully. <|eot_id|><|start_header_id|>user<|end_header_id|> Here is the Description of a dataset. Description:'This collection contains photos of the original, handwritten admissions ledgers (1856-1920--), general case histories (1887-1920--), and typescripts of medical staff meetings (1916-1917) held at the State Archives of North Carolina. All these records are publicly available under the North Carolina Public Records Act, which provides that state records created at least 100 years ago may be accessed and copied by the public. The admissions ledgers (Vols 1, 2, and 3), General Case Books (Vols 13-32), and Medical Meeting Minutes (Vol 9) were originally the property of Dorothea Dix Hospital (1959), also known as the North Carolina Asylum for the Insane (1856), the North Carolina Insane Asylum (1879), the Central Hospital for the Insane (1897), and the State Hospital at Raleigh (1899). As per historical finding aid at the State A' . Please return only a json list of at most 3 Keywords corresponding to the Description:.<|eot_id|><|start_header_id|>assistant<|end_header_id|> {"Answer" : ["History of Medicine","Mental illness","Mental illness-diagnosis","Mentally ill--Care--North Carolina","Psychiatric hospital patients","Psychiatric hospitals","Psychiatric hospitals--North Carolina--Raleigh","Psychiatric hospitals--Records"]} <|eot_id|> | Here is the Description of a dataset. Description:'This collection contains photos of the original, handwritten admissions ledgers (1856-1920--), general case histories (1887-1920--), and typescripts of medical staff meetings (1916-1917) held at the State Archives of North Carolina. All these records are publicly available under the North Carolina Public Records Act, which provides that state records created at least 100 years ago may be accessed and copied by the public. The admissions ledgers (Vols 1, 2, and 3), General Case Books (Vols 13-32), and Medical Meeting Minutes (Vol 9) were originally the property of Dorothea Dix Hospital (1959), also known as the North Carolina Asylum for the Insane (1856), the North Carolina Insane Asylum (1879), the Central Hospital for the Insane (1897), and the State Hospital at Raleigh (1899). As per historical finding aid at the State A' . Please return only a json list of at most 3 Keywords corresponding to the Description:. | This collection contains photos of the original, handwritten admissions ledgers (1856-1920--), general case histories (1887-1920--), and typescripts of medical staff meetings (1916-1917) held at the State Archives of North Carolina. All these records are publicly available under the North Carolina Public Records Act, which provides that state records created at least 100 years ago may be accessed and copied by the public. The admissions ledgers (Vols 1, 2, and 3), General Case Books (Vols 13-32), and Medical Meeting Minutes (Vol 9) were originally the property of Dorothea Dix Hospital (1959), also known as the North Carolina Asylum for the Insane (1856), the North Carolina Insane Asylum (1879), the Central Hospital for the Insane (1897), and the State Hospital at Raleigh (1899). As per historical finding aid at the State A | Arts and Humanities | History of Medicine; Mental illness; Mental illness-diagnosis; Mentally ill--Care--North Carolina; Psychiatric hospital patients; Psychiatric hospitals; Psychiatric hospitals--North Carolina--Raleigh; Psychiatric hospitals--Records |
doi:10.15139/S3/GTCNT3 | Dorothea Dix Hospital Records Collection, 1856-1919 | <|begin_of_text|><|start_header_id|>system<|end_header_id|> You are a research archivist expert in dataset metadata. Answer the question truthfully. <|eot_id|><|start_header_id|>user<|end_header_id|> Here is the Description of a dataset. Description:'This collection contains photos of the original, handwritten admissions ledgers (1856-1920--), general case histories (1887-1920--), and typescripts of medical staff meetings (1916-1917) held at the State Archives of North Carolina. All these records are publicly available under the North Carolina Public Records Act, which provides that state records created at least 100 years ago may be accessed and copied by the public. The admissions ledgers (Vols 1, 2, and 3), General Case Books (Vols 13-32), and Medical Meeting Minutes (Vol 9) were originally the property of Dorothea Dix Hospital (1959), also known as the North Carolina Asylum for the Insane (1856), the North Carolina Insane Asylum (1879), the Central Hospital for the Insane (1897), and the State Hospital at Raleigh (1899). As per historical finding aid at the State A' . Please return only a json list of at most 3 Keywords corresponding to the Description:.<|eot_id|><|start_header_id|>assistant<|end_header_id|> {"Answer" : ["History of Medicine","Mental illness","Mental illness-diagnosis","Mentally ill--Care--North Carolina","Psychiatric hospital patients","Psychiatric hospitals","Psychiatric hospitals--North Carolina--Raleigh","Psychiatric hospitals--Records"]} <|eot_id|> | Here is the Description of a dataset. Description:'This collection contains photos of the original, handwritten admissions ledgers (1856-1920--), general case histories (1887-1920--), and typescripts of medical staff meetings (1916-1917) held at the State Archives of North Carolina. All these records are publicly available under the North Carolina Public Records Act, which provides that state records created at least 100 years ago may be accessed and copied by the public. The admissions ledgers (Vols 1, 2, and 3), General Case Books (Vols 13-32), and Medical Meeting Minutes (Vol 9) were originally the property of Dorothea Dix Hospital (1959), also known as the North Carolina Asylum for the Insane (1856), the North Carolina Insane Asylum (1879), the Central Hospital for the Insane (1897), and the State Hospital at Raleigh (1899). As per historical finding aid at the State A' . Please return only a json list of at most 3 Keywords corresponding to the Description:. | This collection contains photos of the original, handwritten admissions ledgers (1856-1920--), general case histories (1887-1920--), and typescripts of medical staff meetings (1916-1917) held at the State Archives of North Carolina. All these records are publicly available under the North Carolina Public Records Act, which provides that state records created at least 100 years ago may be accessed and copied by the public. The admissions ledgers (Vols 1, 2, and 3), General Case Books (Vols 13-32), and Medical Meeting Minutes (Vol 9) were originally the property of Dorothea Dix Hospital (1959), also known as the North Carolina Asylum for the Insane (1856), the North Carolina Insane Asylum (1879), the Central Hospital for the Insane (1897), and the State Hospital at Raleigh (1899). As per historical finding aid at the State A | Medicine, Health and Life Sciences | History of Medicine; Mental illness; Mental illness-diagnosis; Mentally ill--Care--North Carolina; Psychiatric hospital patients; Psychiatric hospitals; Psychiatric hospitals--North Carolina--Raleigh; Psychiatric hospitals--Records |
doi:10.15139/S3/GTCNT3 | Dorothea Dix Hospital Records Collection, 1856-1919 | <|begin_of_text|><|start_header_id|>system<|end_header_id|> You are a research archivist expert in dataset metadata. Answer the question truthfully. <|eot_id|><|start_header_id|>user<|end_header_id|> Here is the Description of a dataset. Description:'This collection contains photos of the original, handwritten admissions ledgers (1856-1920--), general case histories (1887-1920--), and typescripts of medical staff meetings (1916-1917) held at the State Archives of North Carolina. All these records are publicly available under the North Carolina Public Records Act, which provides that state records created at least 100 years ago may be accessed and copied by the public. The admissions ledgers (Vols 1, 2, and 3), General Case Books (Vols 13-32), and Medical Meeting Minutes (Vol 9) were originally the property of Dorothea Dix Hospital (1959), also known as the North Carolina Asylum for the Insane (1856), the North Carolina Insane Asylum (1879), the Central Hospital for the Insane (1897), and the State Hospital at Raleigh (1899). As per historical finding aid at the State A' . Please return only a json list of at most 3 Keywords corresponding to the Description:.<|eot_id|><|start_header_id|>assistant<|end_header_id|> {"Answer" : ["History of Medicine","Mental illness","Mental illness-diagnosis","Mentally ill--Care--North Carolina","Psychiatric hospital patients","Psychiatric hospitals","Psychiatric hospitals--North Carolina--Raleigh","Psychiatric hospitals--Records"]} <|eot_id|> | Here is the Description of a dataset. Description:'This collection contains photos of the original, handwritten admissions ledgers (1856-1920--), general case histories (1887-1920--), and typescripts of medical staff meetings (1916-1917) held at the State Archives of North Carolina. All these records are publicly available under the North Carolina Public Records Act, which provides that state records created at least 100 years ago may be accessed and copied by the public. The admissions ledgers (Vols 1, 2, and 3), General Case Books (Vols 13-32), and Medical Meeting Minutes (Vol 9) were originally the property of Dorothea Dix Hospital (1959), also known as the North Carolina Asylum for the Insane (1856), the North Carolina Insane Asylum (1879), the Central Hospital for the Insane (1897), and the State Hospital at Raleigh (1899). As per historical finding aid at the State A' . Please return only a json list of at most 3 Keywords corresponding to the Description:. | This collection contains photos of the original, handwritten admissions ledgers (1856-1920--), general case histories (1887-1920--), and typescripts of medical staff meetings (1916-1917) held at the State Archives of North Carolina. All these records are publicly available under the North Carolina Public Records Act, which provides that state records created at least 100 years ago may be accessed and copied by the public. The admissions ledgers (Vols 1, 2, and 3), General Case Books (Vols 13-32), and Medical Meeting Minutes (Vol 9) were originally the property of Dorothea Dix Hospital (1959), also known as the North Carolina Asylum for the Insane (1856), the North Carolina Insane Asylum (1879), the Central Hospital for the Insane (1897), and the State Hospital at Raleigh (1899). As per historical finding aid at the State A | Social Sciences | History of Medicine; Mental illness; Mental illness-diagnosis; Mentally ill--Care--North Carolina; Psychiatric hospital patients; Psychiatric hospitals; Psychiatric hospitals--North Carolina--Raleigh; Psychiatric hospitals--Records |
doi:10.15139/S3/HEDVDZ | Main Effects | <|begin_of_text|><|start_header_id|>system<|end_header_id|> You are a research archivist expert in dataset metadata. Answer the question truthfully. <|eot_id|><|start_header_id|>user<|end_header_id|> Here is the Description of a dataset. Description:'This dataset covers our main experiment from Aim 2 and Aim 3 of the project' . Please return only a json list of at most 3 Keywords corresponding to the Description:.<|eot_id|><|start_header_id|>assistant<|end_header_id|> {"Answer" : ["cigarette","marketing"]} <|eot_id|> | Here is the Description of a dataset. Description:'This dataset covers our main experiment from Aim 2 and Aim 3 of the project' . Please return only a json list of at most 3 Keywords corresponding to the Description:. | This dataset covers our main experiment from Aim 2 and Aim 3 of the project | Medicine, Health and Life Sciences | cigarette; marketing |
doi:10.15139/S3/IAKUQN | Advancing cancer prevention: Optimizing messages | <|begin_of_text|><|start_header_id|>system<|end_header_id|> You are a research archivist expert in dataset metadata. Answer the question truthfully. <|eot_id|><|start_header_id|>user<|end_header_id|> Here is the Description of a dataset. Description:'This is a multi-site study funded by Cancer Research UK through a Cancer Research UK/National Cancer Institute Knowledge Integration Sandpit. Half of the qualitative interviews will be conducted by ECU. The main quantitative survey will be conducted by ECU. Qualitative analysis will be conducted by University of Glasgow. The qualitative study will inform the design of the quantitative study. Quantitative analysis will be conducted by Florida International University. University College London will conduct a small pilot experiment also using Qualtrics Panels. BACKGROUNDTobacco, alcohol, and sugar consumption contribute to cancer burden. An evidence-based population-level intervention to reduce intake of tobacco, alcohol, and sugar-added products is the implementation of policies that increase their price. This can be done thr' . Please return only a json list of at most 3 Keywords corresponding to the Description:.<|eot_id|><|start_header_id|>assistant<|end_header_id|> {"Answer" : ["cancer","communications","message framing","price promotions"]} <|eot_id|> | Here is the Description of a dataset. Description:'This is a multi-site study funded by Cancer Research UK through a Cancer Research UK/National Cancer Institute Knowledge Integration Sandpit. Half of the qualitative interviews will be conducted by ECU. The main quantitative survey will be conducted by ECU. Qualitative analysis will be conducted by University of Glasgow. The qualitative study will inform the design of the quantitative study. Quantitative analysis will be conducted by Florida International University. University College London will conduct a small pilot experiment also using Qualtrics Panels. BACKGROUNDTobacco, alcohol, and sugar consumption contribute to cancer burden. An evidence-based population-level intervention to reduce intake of tobacco, alcohol, and sugar-added products is the implementation of policies that increase their price. This can be done thr' . Please return only a json list of at most 3 Keywords corresponding to the Description:. | This is a multi-site study funded by Cancer Research UK through a Cancer Research UK/National Cancer Institute Knowledge Integration Sandpit. Half of the qualitative interviews will be conducted by ECU. The main quantitative survey will be conducted by ECU. Qualitative analysis will be conducted by University of Glasgow. The qualitative study will inform the design of the quantitative study. Quantitative analysis will be conducted by Florida International University. University College London will conduct a small pilot experiment also using Qualtrics Panels. BACKGROUNDTobacco, alcohol, and sugar consumption contribute to cancer burden. An evidence-based population-level intervention to reduce intake of tobacco, alcohol, and sugar-added products is the implementation of policies that increase their price. This can be done thr | Medicine, Health and Life Sciences | cancer; communications; message framing; price promotions |
doi:10.15139/S3/IAKUQN | Advancing cancer prevention: Optimizing messages | <|begin_of_text|><|start_header_id|>system<|end_header_id|> You are a research archivist expert in dataset metadata. Answer the question truthfully. <|eot_id|><|start_header_id|>user<|end_header_id|> Here is the Description of a dataset. Description:'This is a multi-site study funded by Cancer Research UK through a Cancer Research UK/National Cancer Institute Knowledge Integration Sandpit. Half of the qualitative interviews will be conducted by ECU. The main quantitative survey will be conducted by ECU. Qualitative analysis will be conducted by University of Glasgow. The qualitative study will inform the design of the quantitative study. Quantitative analysis will be conducted by Florida International University. University College London will conduct a small pilot experiment also using Qualtrics Panels. BACKGROUNDTobacco, alcohol, and sugar consumption contribute to cancer burden. An evidence-based population-level intervention to reduce intake of tobacco, alcohol, and sugar-added products is the implementation of policies that increase their price. This can be done thr' . Please return only a json list of at most 3 Keywords corresponding to the Description:.<|eot_id|><|start_header_id|>assistant<|end_header_id|> {"Answer" : ["cancer","communications","message framing","price promotions"]} <|eot_id|> | Here is the Description of a dataset. Description:'This is a multi-site study funded by Cancer Research UK through a Cancer Research UK/National Cancer Institute Knowledge Integration Sandpit. Half of the qualitative interviews will be conducted by ECU. The main quantitative survey will be conducted by ECU. Qualitative analysis will be conducted by University of Glasgow. The qualitative study will inform the design of the quantitative study. Quantitative analysis will be conducted by Florida International University. University College London will conduct a small pilot experiment also using Qualtrics Panels. BACKGROUNDTobacco, alcohol, and sugar consumption contribute to cancer burden. An evidence-based population-level intervention to reduce intake of tobacco, alcohol, and sugar-added products is the implementation of policies that increase their price. This can be done thr' . Please return only a json list of at most 3 Keywords corresponding to the Description:. | This is a multi-site study funded by Cancer Research UK through a Cancer Research UK/National Cancer Institute Knowledge Integration Sandpit. Half of the qualitative interviews will be conducted by ECU. The main quantitative survey will be conducted by ECU. Qualitative analysis will be conducted by University of Glasgow. The qualitative study will inform the design of the quantitative study. Quantitative analysis will be conducted by Florida International University. University College London will conduct a small pilot experiment also using Qualtrics Panels. BACKGROUNDTobacco, alcohol, and sugar consumption contribute to cancer burden. An evidence-based population-level intervention to reduce intake of tobacco, alcohol, and sugar-added products is the implementation of policies that increase their price. This can be done thr | Social Sciences | cancer; communications; message framing; price promotions |
doi:10.15139/S3/IGSF54 | Continuous quality improvement of safe water storage containers: a cluster randomized trial in rural Burkina Faso | <|begin_of_text|><|start_header_id|>system<|end_header_id|> You are a research archivist expert in dataset metadata. Answer the question truthfully. <|eot_id|><|start_header_id|>user<|end_header_id|> Here is the Description of a dataset. Description:'Safe storage protects household drinking water from contamination, maintaining water quality and preventing diarrheal and other water-borne diseases. However, achieving high adoption and sustained used of safe storage is challenging. We developed a safe water storage container (SWSC) intervention using the Lean Six Sigma continuous quality improvement framework in rural Ghana to optimize adoption and water quality, and subsequently adapted the SWSC for implementation in Burkina Faso. This study reports the impacts of the adapted Burkinabe SWSC on Escherichia coli contamination in household stored water in a cluster randomized trial with 49 intervention villages (274 households) and 50 no-intervention control (290 households).Metadata is included as the first sheet of the Excel file. This trial was funded by WaterAid and the Conrad N' . Please return only a json list of at most 3 Keywords corresponding to the Description:.<|eot_id|><|start_header_id|>assistant<|end_header_id|> {"Answer" : ["water quality, safe storage, WaSH, continuous quality improvement, CQI, adaptation"]} <|eot_id|> | Here is the Description of a dataset. Description:'Safe storage protects household drinking water from contamination, maintaining water quality and preventing diarrheal and other water-borne diseases. However, achieving high adoption and sustained used of safe storage is challenging. We developed a safe water storage container (SWSC) intervention using the Lean Six Sigma continuous quality improvement framework in rural Ghana to optimize adoption and water quality, and subsequently adapted the SWSC for implementation in Burkina Faso. This study reports the impacts of the adapted Burkinabe SWSC on Escherichia coli contamination in household stored water in a cluster randomized trial with 49 intervention villages (274 households) and 50 no-intervention control (290 households).Metadata is included as the first sheet of the Excel file. This trial was funded by WaterAid and the Conrad N' . Please return only a json list of at most 3 Keywords corresponding to the Description:. | Safe storage protects household drinking water from contamination, maintaining water quality and preventing diarrheal and other water-borne diseases. However, achieving high adoption and sustained used of safe storage is challenging. We developed a safe water storage container (SWSC) intervention using the Lean Six Sigma continuous quality improvement framework in rural Ghana to optimize adoption and water quality, and subsequently adapted the SWSC for implementation in Burkina Faso. This study reports the impacts of the adapted Burkinabe SWSC on Escherichia coli contamination in household stored water in a cluster randomized trial with 49 intervention villages (274 households) and 50 no-intervention control (290 households).Metadata is included as the first sheet of the Excel file. This trial was funded by WaterAid and the Conrad N | Medicine, Health and Life Sciences | water quality, safe storage, WaSH, continuous quality improvement, CQI, adaptation |
doi:10.15139/S3/IGSF54 | Continuous quality improvement of safe water storage containers: a cluster randomized trial in rural Burkina Faso | <|begin_of_text|><|start_header_id|>system<|end_header_id|> You are a research archivist expert in dataset metadata. Answer the question truthfully. <|eot_id|><|start_header_id|>user<|end_header_id|> Here is the Description of a dataset. Description:'Safe storage protects household drinking water from contamination, maintaining water quality and preventing diarrheal and other water-borne diseases. However, achieving high adoption and sustained used of safe storage is challenging. We developed a safe water storage container (SWSC) intervention using the Lean Six Sigma continuous quality improvement framework in rural Ghana to optimize adoption and water quality, and subsequently adapted the SWSC for implementation in Burkina Faso. This study reports the impacts of the adapted Burkinabe SWSC on Escherichia coli contamination in household stored water in a cluster randomized trial with 49 intervention villages (274 households) and 50 no-intervention control (290 households).Metadata is included as the first sheet of the Excel file. This trial was funded by WaterAid and the Conrad N' . Please return only a json list of at most 3 Keywords corresponding to the Description:.<|eot_id|><|start_header_id|>assistant<|end_header_id|> {"Answer" : ["water quality, safe storage, WaSH, continuous quality improvement, CQI, adaptation"]} <|eot_id|> | Here is the Description of a dataset. Description:'Safe storage protects household drinking water from contamination, maintaining water quality and preventing diarrheal and other water-borne diseases. However, achieving high adoption and sustained used of safe storage is challenging. We developed a safe water storage container (SWSC) intervention using the Lean Six Sigma continuous quality improvement framework in rural Ghana to optimize adoption and water quality, and subsequently adapted the SWSC for implementation in Burkina Faso. This study reports the impacts of the adapted Burkinabe SWSC on Escherichia coli contamination in household stored water in a cluster randomized trial with 49 intervention villages (274 households) and 50 no-intervention control (290 households).Metadata is included as the first sheet of the Excel file. This trial was funded by WaterAid and the Conrad N' . Please return only a json list of at most 3 Keywords corresponding to the Description:. | Safe storage protects household drinking water from contamination, maintaining water quality and preventing diarrheal and other water-borne diseases. However, achieving high adoption and sustained used of safe storage is challenging. We developed a safe water storage container (SWSC) intervention using the Lean Six Sigma continuous quality improvement framework in rural Ghana to optimize adoption and water quality, and subsequently adapted the SWSC for implementation in Burkina Faso. This study reports the impacts of the adapted Burkinabe SWSC on Escherichia coli contamination in household stored water in a cluster randomized trial with 49 intervention villages (274 households) and 50 no-intervention control (290 households).Metadata is included as the first sheet of the Excel file. This trial was funded by WaterAid and the Conrad N | Social Sciences | water quality, safe storage, WaSH, continuous quality improvement, CQI, adaptation |
doi:10.15139/S3/IGWLMU | Patient Education Materials | <|begin_of_text|><|start_header_id|>system<|end_header_id|> You are a research archivist expert in dataset metadata. Answer the question truthfully. <|eot_id|><|start_header_id|>user<|end_header_id|> Here is the Description of a dataset. Description:'Patient Education Materials collected and stored (with permission) as part of the 'Addressing migrant and seasonal farmworker health disparities with information resources' project' . Please return only a json list of at most 3 Keywords corresponding to the Description:.<|eot_id|><|start_header_id|>assistant<|end_header_id|> {"Answer" : ["farmworkers","patient education materials"]} <|eot_id|> | Here is the Description of a dataset. Description:'Patient Education Materials collected and stored (with permission) as part of the 'Addressing migrant and seasonal farmworker health disparities with information resources' project' . Please return only a json list of at most 3 Keywords corresponding to the Description:. | Patient Education Materials collected and stored (with permission) as part of the 'Addressing migrant and seasonal farmworker health disparities with information resources' project | Medicine, Health and Life Sciences | farmworkers; patient education materials |
doi:10.15139/S3/IURHL6 | TB/HIV-Mobility Study in East Africa | <|begin_of_text|><|start_header_id|>system<|end_header_id|> You are a research archivist expert in dataset metadata. Answer the question truthfully. <|eot_id|><|start_header_id|>user<|end_header_id|> Here is the Description of a dataset. Description:'These data were collected for a 2019 study to understand mobility patterns, treatment outcomes, and the feasibility of regional tracing strategies among patients in care for HIV and/or TB in the Lake Victoria region. The study was funded by the United States Agency for International Development and the United States President’s Emergency Plan for AIDS Relief and was led by MEASURE Evaluation in collaboration with local partners from the Lake Victoria Consortium for Health Research: Uganda Virus Research Institute and the International AIDS Vaccine Initiative; Kenya Medical Research Institute; Medical Research Council/Uganda Virus Research Institute and the London School of Hygiene and Tropical Medicine; and the Mwanza Intervention Trials Unit' . Please return only a json list of at most 3 Keywords corresponding to the Description:.<|eot_id|><|start_header_id|>assistant<|end_header_id|> {"Answer" : ["East Africa","Facility-based survey","Facility data","HIV","Morbility","TB"]} <|eot_id|> | Here is the Description of a dataset. Description:'These data were collected for a 2019 study to understand mobility patterns, treatment outcomes, and the feasibility of regional tracing strategies among patients in care for HIV and/or TB in the Lake Victoria region. The study was funded by the United States Agency for International Development and the United States President’s Emergency Plan for AIDS Relief and was led by MEASURE Evaluation in collaboration with local partners from the Lake Victoria Consortium for Health Research: Uganda Virus Research Institute and the International AIDS Vaccine Initiative; Kenya Medical Research Institute; Medical Research Council/Uganda Virus Research Institute and the London School of Hygiene and Tropical Medicine; and the Mwanza Intervention Trials Unit' . Please return only a json list of at most 3 Keywords corresponding to the Description:. | These data were collected for a 2019 study to understand mobility patterns, treatment outcomes, and the feasibility of regional tracing strategies among patients in care for HIV and/or TB in the Lake Victoria region. The study was funded by the United States Agency for International Development and the United States President’s Emergency Plan for AIDS Relief and was led by MEASURE Evaluation in collaboration with local partners from the Lake Victoria Consortium for Health Research: Uganda Virus Research Institute and the International AIDS Vaccine Initiative; Kenya Medical Research Institute; Medical Research Council/Uganda Virus Research Institute and the London School of Hygiene and Tropical Medicine; and the Mwanza Intervention Trials Unit | Medicine, Health and Life Sciences | East Africa; Facility-based survey; Facility data; HIV; Morbility; TB |
doi:10.15139/S3/J6BOUB | Digital Health Literacy Community Workshop Materials | <|begin_of_text|><|start_header_id|>system<|end_header_id|> You are a research archivist expert in dataset metadata. Answer the question truthfully. <|eot_id|><|start_header_id|>user<|end_header_id|> Here is the Description of a dataset. Description:'Materials inclusive of a powerpoint, handouts, and scripts in English and Spanish. Can be reused with acknowledgement of the creators and grant numbers. Use the materials to hold your own online or in person digital health literacy workshop. Original materials were generated by a partnership with NNLM All of Us and the Wisconsin Health Literacy programs' . Please return only a json list of at most 3 Keywords corresponding to the Description:.<|eot_id|><|start_header_id|>assistant<|end_header_id|> {"Answer" : ["digital divide","health literacy"]} <|eot_id|> | Here is the Description of a dataset. Description:'Materials inclusive of a powerpoint, handouts, and scripts in English and Spanish. Can be reused with acknowledgement of the creators and grant numbers. Use the materials to hold your own online or in person digital health literacy workshop. Original materials were generated by a partnership with NNLM All of Us and the Wisconsin Health Literacy programs' . Please return only a json list of at most 3 Keywords corresponding to the Description:. | Materials inclusive of a powerpoint, handouts, and scripts in English and Spanish. Can be reused with acknowledgement of the creators and grant numbers. Use the materials to hold your own online or in person digital health literacy workshop. Original materials were generated by a partnership with NNLM All of Us and the Wisconsin Health Literacy programs | Computer and Information Science | digital divide; health literacy |
doi:10.15139/S3/J6BOUB | Digital Health Literacy Community Workshop Materials | <|begin_of_text|><|start_header_id|>system<|end_header_id|> You are a research archivist expert in dataset metadata. Answer the question truthfully. <|eot_id|><|start_header_id|>user<|end_header_id|> Here is the Description of a dataset. Description:'Materials inclusive of a powerpoint, handouts, and scripts in English and Spanish. Can be reused with acknowledgement of the creators and grant numbers. Use the materials to hold your own online or in person digital health literacy workshop. Original materials were generated by a partnership with NNLM All of Us and the Wisconsin Health Literacy programs' . Please return only a json list of at most 3 Keywords corresponding to the Description:.<|eot_id|><|start_header_id|>assistant<|end_header_id|> {"Answer" : ["digital divide","health literacy"]} <|eot_id|> | Here is the Description of a dataset. Description:'Materials inclusive of a powerpoint, handouts, and scripts in English and Spanish. Can be reused with acknowledgement of the creators and grant numbers. Use the materials to hold your own online or in person digital health literacy workshop. Original materials were generated by a partnership with NNLM All of Us and the Wisconsin Health Literacy programs' . Please return only a json list of at most 3 Keywords corresponding to the Description:. | Materials inclusive of a powerpoint, handouts, and scripts in English and Spanish. Can be reused with acknowledgement of the creators and grant numbers. Use the materials to hold your own online or in person digital health literacy workshop. Original materials were generated by a partnership with NNLM All of Us and the Wisconsin Health Literacy programs | Medicine, Health and Life Sciences | digital divide; health literacy |
doi:10.15139/S3/JE7INQ | Development of novel survey methodology for remapping LF in low-prevalence areas | <|begin_of_text|><|start_header_id|>system<|end_header_id|> You are a research archivist expert in dataset metadata. Answer the question truthfully. <|eot_id|><|start_header_id|>user<|end_header_id|> Here is the Description of a dataset. Description:'Research Objectives: 1)Demonstrate the utility of a new mapping strategy based on school cluster random sampling Using PPES. 2)Assess the value of laboratory-based antibody assays as confirmatory tests and additional diagnostic tools for measuring LF transmission' . Please return only a json list of at most 3 Keywords corresponding to the Description:.<|eot_id|><|start_header_id|>assistant<|end_header_id|> {"Answer" : ["Immunochromatographic Test (ICT)","Lymphatic Filariasis","Wb123 ELISA"]} <|eot_id|> | Here is the Description of a dataset. Description:'Research Objectives: 1)Demonstrate the utility of a new mapping strategy based on school cluster random sampling Using PPES. 2)Assess the value of laboratory-based antibody assays as confirmatory tests and additional diagnostic tools for measuring LF transmission' . Please return only a json list of at most 3 Keywords corresponding to the Description:. | Research Objectives: 1)Demonstrate the utility of a new mapping strategy based on school cluster random sampling Using PPES. 2)Assess the value of laboratory-based antibody assays as confirmatory tests and additional diagnostic tools for measuring LF transmission | Medicine, Health and Life Sciences | Immunochromatographic Test (ICT); Lymphatic Filariasis; Wb123 ELISA |
doi:10.15139/S3/JLTQDI | North Carolina Vital Statistics -- Deaths 2018 | <|begin_of_text|><|start_header_id|>system<|end_header_id|> You are a research archivist expert in dataset metadata. Answer the question truthfully. <|eot_id|><|start_header_id|>user<|end_header_id|> Here is the Description of a dataset. Description:'The North Carolina State Center for Health Services (SCHS) collects yearly vital statistics. The Odum Institute holds vital statistics beginning in 1968 for deaths, marriages and divorce. Public marriage and divorce data are available through 1999 only. Vital statistics for births, fetal deaths, and birth/infant deaths may be obtained directly from SCHS by submitting a request to [email protected] study focuses on deaths in North Carolina in 2018. Death is defined as the permanent disappearance of any evidence of life at any time after live birth. This definition excludes fetal deaths. The data kept for deaths includes the age, race, marital status, and sex of the individual; date, time, cause and location of death; and mode of burial.Minor changes to the files beginning in 2014 reflect the release o' . Please return only a json list of at most 3 Keywords corresponding to the Description:.<|eot_id|><|start_header_id|>assistant<|end_header_id|> {"Answer" : ["Death","Vital statistics"]} <|eot_id|> | Here is the Description of a dataset. Description:'The North Carolina State Center for Health Services (SCHS) collects yearly vital statistics. The Odum Institute holds vital statistics beginning in 1968 for deaths, marriages and divorce. Public marriage and divorce data are available through 1999 only. Vital statistics for births, fetal deaths, and birth/infant deaths may be obtained directly from SCHS by submitting a request to [email protected] study focuses on deaths in North Carolina in 2018. Death is defined as the permanent disappearance of any evidence of life at any time after live birth. This definition excludes fetal deaths. The data kept for deaths includes the age, race, marital status, and sex of the individual; date, time, cause and location of death; and mode of burial.Minor changes to the files beginning in 2014 reflect the release o' . Please return only a json list of at most 3 Keywords corresponding to the Description:. | The North Carolina State Center for Health Services (SCHS) collects yearly vital statistics. The Odum Institute holds vital statistics beginning in 1968 for deaths, marriages and divorce. Public marriage and divorce data are available through 1999 only. Vital statistics for births, fetal deaths, and birth/infant deaths may be obtained directly from SCHS by submitting a request to [email protected] study focuses on deaths in North Carolina in 2018. Death is defined as the permanent disappearance of any evidence of life at any time after live birth. This definition excludes fetal deaths. The data kept for deaths includes the age, race, marital status, and sex of the individual; date, time, cause and location of death; and mode of burial.Minor changes to the files beginning in 2014 reflect the release o | Medicine, Health and Life Sciences | Death; Vital statistics |
doi:10.15139/S3/JLTQDI | North Carolina Vital Statistics -- Deaths 2018 | <|begin_of_text|><|start_header_id|>system<|end_header_id|> You are a research archivist expert in dataset metadata. Answer the question truthfully. <|eot_id|><|start_header_id|>user<|end_header_id|> Here is the Description of a dataset. Description:'The North Carolina State Center for Health Services (SCHS) collects yearly vital statistics. The Odum Institute holds vital statistics beginning in 1968 for deaths, marriages and divorce. Public marriage and divorce data are available through 1999 only. Vital statistics for births, fetal deaths, and birth/infant deaths may be obtained directly from SCHS by submitting a request to [email protected] study focuses on deaths in North Carolina in 2018. Death is defined as the permanent disappearance of any evidence of life at any time after live birth. This definition excludes fetal deaths. The data kept for deaths includes the age, race, marital status, and sex of the individual; date, time, cause and location of death; and mode of burial.Minor changes to the files beginning in 2014 reflect the release o' . Please return only a json list of at most 3 Keywords corresponding to the Description:.<|eot_id|><|start_header_id|>assistant<|end_header_id|> {"Answer" : ["Death","Vital statistics"]} <|eot_id|> | Here is the Description of a dataset. Description:'The North Carolina State Center for Health Services (SCHS) collects yearly vital statistics. The Odum Institute holds vital statistics beginning in 1968 for deaths, marriages and divorce. Public marriage and divorce data are available through 1999 only. Vital statistics for births, fetal deaths, and birth/infant deaths may be obtained directly from SCHS by submitting a request to [email protected] study focuses on deaths in North Carolina in 2018. Death is defined as the permanent disappearance of any evidence of life at any time after live birth. This definition excludes fetal deaths. The data kept for deaths includes the age, race, marital status, and sex of the individual; date, time, cause and location of death; and mode of burial.Minor changes to the files beginning in 2014 reflect the release o' . Please return only a json list of at most 3 Keywords corresponding to the Description:. | The North Carolina State Center for Health Services (SCHS) collects yearly vital statistics. The Odum Institute holds vital statistics beginning in 1968 for deaths, marriages and divorce. Public marriage and divorce data are available through 1999 only. Vital statistics for births, fetal deaths, and birth/infant deaths may be obtained directly from SCHS by submitting a request to [email protected] study focuses on deaths in North Carolina in 2018. Death is defined as the permanent disappearance of any evidence of life at any time after live birth. This definition excludes fetal deaths. The data kept for deaths includes the age, race, marital status, and sex of the individual; date, time, cause and location of death; and mode of burial.Minor changes to the files beginning in 2014 reflect the release o | Social Sciences | Death; Vital statistics |
doi:10.15139/S3/JNW5XE | Migrant and Seasonal Farmworker Health Research Mapping Review Bibliographies | <|begin_of_text|><|start_header_id|>system<|end_header_id|> You are a research archivist expert in dataset metadata. Answer the question truthfully. <|eot_id|><|start_header_id|>user<|end_header_id|> Here is the Description of a dataset. Description:'Bibliographies from mapping review project.Research reported in this publication was supported by the National Library of Medicine of the National Institutes of Health under Award Number G08LM013198. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health' . Please return only a json list of at most 3 Keywords corresponding to the Description:.<|eot_id|><|start_header_id|>assistant<|end_header_id|> {"Answer" : ["farmworker","farmworkers","research"]} <|eot_id|> | Here is the Description of a dataset. Description:'Bibliographies from mapping review project.Research reported in this publication was supported by the National Library of Medicine of the National Institutes of Health under Award Number G08LM013198. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health' . Please return only a json list of at most 3 Keywords corresponding to the Description:. | Bibliographies from mapping review project.Research reported in this publication was supported by the National Library of Medicine of the National Institutes of Health under Award Number G08LM013198. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health | Medicine, Health and Life Sciences | farmworker; farmworkers; research |
doi:10.15139/S3/JUUSHC | Simulating the effect of evaluation unit size on eligibility to stop mass drug administration for lymphatic filariasis in Haiti | <|begin_of_text|><|start_header_id|>system<|end_header_id|> You are a research archivist expert in dataset metadata. Answer the question truthfully. <|eot_id|><|start_header_id|>user<|end_header_id|> Here is the Description of a dataset. Description:'Existing guidelines for delimiting the geographic areas to conduct transmission assessment surveys (TAS) permit large evaluation units. In 2015, TASs were conducted in Haiti using more stringent criteria for forming evaluation units, resulting in much smaller geographic areas for evaluation. Using simulations, the authors found that, had Haiti followed the existing guidelines and assessed larger geographic areas, many of the areas might have been misclassified and mass drug administration would have been stopped prematurely in some settings. Simulations of mini-TAS, a strategy with smaller power and hence smaller sample size than TAS, resulted in more conservative “passing” and “failing” when implemented in original evaluation units. This research suggests that caution is needed when forming evaluation units for TAS, especially if the p' . Please return only a json list of at most 3 Keywords corresponding to the Description:.<|eot_id|><|start_header_id|>assistant<|end_header_id|> {"Answer" : ["Evaluation Unit","Lymphatic Filariasis","Transmission Assessment Survey"]} <|eot_id|> | Here is the Description of a dataset. Description:'Existing guidelines for delimiting the geographic areas to conduct transmission assessment surveys (TAS) permit large evaluation units. In 2015, TASs were conducted in Haiti using more stringent criteria for forming evaluation units, resulting in much smaller geographic areas for evaluation. Using simulations, the authors found that, had Haiti followed the existing guidelines and assessed larger geographic areas, many of the areas might have been misclassified and mass drug administration would have been stopped prematurely in some settings. Simulations of mini-TAS, a strategy with smaller power and hence smaller sample size than TAS, resulted in more conservative “passing” and “failing” when implemented in original evaluation units. This research suggests that caution is needed when forming evaluation units for TAS, especially if the p' . Please return only a json list of at most 3 Keywords corresponding to the Description:. | Existing guidelines for delimiting the geographic areas to conduct transmission assessment surveys (TAS) permit large evaluation units. In 2015, TASs were conducted in Haiti using more stringent criteria for forming evaluation units, resulting in much smaller geographic areas for evaluation. Using simulations, the authors found that, had Haiti followed the existing guidelines and assessed larger geographic areas, many of the areas might have been misclassified and mass drug administration would have been stopped prematurely in some settings. Simulations of mini-TAS, a strategy with smaller power and hence smaller sample size than TAS, resulted in more conservative “passing” and “failing” when implemented in original evaluation units. This research suggests that caution is needed when forming evaluation units for TAS, especially if the p | Medicine, Health and Life Sciences | Evaluation Unit; Lymphatic Filariasis; Transmission Assessment Survey |
doi:10.15139/S3/KKQ9NE | Dataset for Mixtures Modeling Identifies Chemical Inducers versus Repressors of Toxicity associated with Wildfire Smoke | <|begin_of_text|><|start_header_id|>system<|end_header_id|> You are a research archivist expert in dataset metadata. Answer the question truthfully. <|eot_id|><|start_header_id|>user<|end_header_id|> Here is the Description of a dataset. Description:'This dataset includes chemistry measures across 12 biomass burn scenarios (serving as lab-based simulations of potential environmental exposures) and mouse cardiopulmonary toxicology measures collected from mice exposed to the same 12 biomass burn scenarios. Files are organized into four separate .csv files, containing either the measured values or the associated metadata, with descriptive labels included throughout' . Please return only a json list of at most 3 Keywords corresponding to the Description:.<|eot_id|><|start_header_id|>assistant<|end_header_id|> {"Answer" : ["Air Pollution","Biomass burns","Mixtures","Mixtures Toxicology","Pulmonary biology","Toxicity","Wildfire"]} <|eot_id|> | Here is the Description of a dataset. Description:'This dataset includes chemistry measures across 12 biomass burn scenarios (serving as lab-based simulations of potential environmental exposures) and mouse cardiopulmonary toxicology measures collected from mice exposed to the same 12 biomass burn scenarios. Files are organized into four separate .csv files, containing either the measured values or the associated metadata, with descriptive labels included throughout' . Please return only a json list of at most 3 Keywords corresponding to the Description:. | This dataset includes chemistry measures across 12 biomass burn scenarios (serving as lab-based simulations of potential environmental exposures) and mouse cardiopulmonary toxicology measures collected from mice exposed to the same 12 biomass burn scenarios. Files are organized into four separate .csv files, containing either the measured values or the associated metadata, with descriptive labels included throughout | Chemistry | Air Pollution; Biomass burns; Mixtures; Mixtures Toxicology; Pulmonary biology; Toxicity; Wildfire |
doi:10.15139/S3/KKQ9NE | Dataset for Mixtures Modeling Identifies Chemical Inducers versus Repressors of Toxicity associated with Wildfire Smoke | <|begin_of_text|><|start_header_id|>system<|end_header_id|> You are a research archivist expert in dataset metadata. Answer the question truthfully. <|eot_id|><|start_header_id|>user<|end_header_id|> Here is the Description of a dataset. Description:'This dataset includes chemistry measures across 12 biomass burn scenarios (serving as lab-based simulations of potential environmental exposures) and mouse cardiopulmonary toxicology measures collected from mice exposed to the same 12 biomass burn scenarios. Files are organized into four separate .csv files, containing either the measured values or the associated metadata, with descriptive labels included throughout' . Please return only a json list of at most 3 Keywords corresponding to the Description:.<|eot_id|><|start_header_id|>assistant<|end_header_id|> {"Answer" : ["Air Pollution","Biomass burns","Mixtures","Mixtures Toxicology","Pulmonary biology","Toxicity","Wildfire"]} <|eot_id|> | Here is the Description of a dataset. Description:'This dataset includes chemistry measures across 12 biomass burn scenarios (serving as lab-based simulations of potential environmental exposures) and mouse cardiopulmonary toxicology measures collected from mice exposed to the same 12 biomass burn scenarios. Files are organized into four separate .csv files, containing either the measured values or the associated metadata, with descriptive labels included throughout' . Please return only a json list of at most 3 Keywords corresponding to the Description:. | This dataset includes chemistry measures across 12 biomass burn scenarios (serving as lab-based simulations of potential environmental exposures) and mouse cardiopulmonary toxicology measures collected from mice exposed to the same 12 biomass burn scenarios. Files are organized into four separate .csv files, containing either the measured values or the associated metadata, with descriptive labels included throughout | Earth and Environmental Sciences | Air Pollution; Biomass burns; Mixtures; Mixtures Toxicology; Pulmonary biology; Toxicity; Wildfire |
doi:10.15139/S3/KKQ9NE | Dataset for Mixtures Modeling Identifies Chemical Inducers versus Repressors of Toxicity associated with Wildfire Smoke | <|begin_of_text|><|start_header_id|>system<|end_header_id|> You are a research archivist expert in dataset metadata. Answer the question truthfully. <|eot_id|><|start_header_id|>user<|end_header_id|> Here is the Description of a dataset. Description:'This dataset includes chemistry measures across 12 biomass burn scenarios (serving as lab-based simulations of potential environmental exposures) and mouse cardiopulmonary toxicology measures collected from mice exposed to the same 12 biomass burn scenarios. Files are organized into four separate .csv files, containing either the measured values or the associated metadata, with descriptive labels included throughout' . Please return only a json list of at most 3 Keywords corresponding to the Description:.<|eot_id|><|start_header_id|>assistant<|end_header_id|> {"Answer" : ["Air Pollution","Biomass burns","Mixtures","Mixtures Toxicology","Pulmonary biology","Toxicity","Wildfire"]} <|eot_id|> | Here is the Description of a dataset. Description:'This dataset includes chemistry measures across 12 biomass burn scenarios (serving as lab-based simulations of potential environmental exposures) and mouse cardiopulmonary toxicology measures collected from mice exposed to the same 12 biomass burn scenarios. Files are organized into four separate .csv files, containing either the measured values or the associated metadata, with descriptive labels included throughout' . Please return only a json list of at most 3 Keywords corresponding to the Description:. | This dataset includes chemistry measures across 12 biomass burn scenarios (serving as lab-based simulations of potential environmental exposures) and mouse cardiopulmonary toxicology measures collected from mice exposed to the same 12 biomass burn scenarios. Files are organized into four separate .csv files, containing either the measured values or the associated metadata, with descriptive labels included throughout | Medicine, Health and Life Sciences | Air Pollution; Biomass burns; Mixtures; Mixtures Toxicology; Pulmonary biology; Toxicity; Wildfire |
doi:10.15139/S3/LG7N0Z | District Mapping of Onchocerciasis and Lymphatic Filariasis in Malawi: Assessing Sampling Strategies for Onchocerciasis Elimination Mapping (OEM) | <|begin_of_text|><|start_header_id|>system<|end_header_id|> You are a research archivist expert in dataset metadata. Answer the question truthfully. <|eot_id|><|start_header_id|>user<|end_header_id|> Here is the Description of a dataset. Description:'As onchocerciasis programs in Africa shift from a paradigm of control to one of elimination, there is a need to determine whether transmission is ongoing in previously-untreated areas. To do so, there is a need to develop a mapping strategy that is rigorous enough to detect low levels of ongoing transmission while also using resources efficiently. A multi-country operational research study was conducted comparing sampling in purposively-selected communities, random sampling in randomly-selected communities, and random sampling in the schools in which the majority of children from the randomly-selected villages attended. In Malawi, quota sampling was used in purposively selected communities. Three districts were included in the study: Chitipa, Dedza, and Karonga. Chitipa had never previously undergone treatment with ivermectin, whereas D' . Please return only a json list of at most 3 Keywords corresponding to the Description:.<|eot_id|><|start_header_id|>assistant<|end_header_id|> {"Answer" : ["Lymphatic Filariasis","Onchocerciasis"]} <|eot_id|> | Here is the Description of a dataset. Description:'As onchocerciasis programs in Africa shift from a paradigm of control to one of elimination, there is a need to determine whether transmission is ongoing in previously-untreated areas. To do so, there is a need to develop a mapping strategy that is rigorous enough to detect low levels of ongoing transmission while also using resources efficiently. A multi-country operational research study was conducted comparing sampling in purposively-selected communities, random sampling in randomly-selected communities, and random sampling in the schools in which the majority of children from the randomly-selected villages attended. In Malawi, quota sampling was used in purposively selected communities. Three districts were included in the study: Chitipa, Dedza, and Karonga. Chitipa had never previously undergone treatment with ivermectin, whereas D' . Please return only a json list of at most 3 Keywords corresponding to the Description:. | As onchocerciasis programs in Africa shift from a paradigm of control to one of elimination, there is a need to determine whether transmission is ongoing in previously-untreated areas. To do so, there is a need to develop a mapping strategy that is rigorous enough to detect low levels of ongoing transmission while also using resources efficiently. A multi-country operational research study was conducted comparing sampling in purposively-selected communities, random sampling in randomly-selected communities, and random sampling in the schools in which the majority of children from the randomly-selected villages attended. In Malawi, quota sampling was used in purposively selected communities. Three districts were included in the study: Chitipa, Dedza, and Karonga. Chitipa had never previously undergone treatment with ivermectin, whereas D | Medicine, Health and Life Sciences | Lymphatic Filariasis; Onchocerciasis |
doi:10.15139/S3/LNTB9R | Dorothea Dix Hospital Admissions Ledger Dataset, Patients 0000-7827 | <|begin_of_text|><|start_header_id|>system<|end_header_id|> You are a research archivist expert in dataset metadata. Answer the question truthfully. <|eot_id|><|start_header_id|>user<|end_header_id|> Here is the Description of a dataset. Description:'This dataset was transcribed from photos of the original, handwritten admissions ledgers for the North Carolina Asylum for the Insane (later known as Dorothea Dix Hospital) held at the State Archives of North Carolina. The original records are publicly available under the North Carolina Public Records Act, which indicates that records created by state government entities more than 100 years ago are publicly accessible through the State Archives of North Carolina. Historical finding aid at the State Archives of North Carolina (1977) notes that admissions ledger was maintained from the opening of the hospital in 1856 to 1937 (Vol. 1: 1856-1911; Vol. 2: 1911-1929; Vol. 3: 1929-1937). For the period relevant here (1856-1920), this was a hand-written ledger recording both the admission (with identifying admissions number) and disposition (di' . Please return only a json list of at most 3 Keywords corresponding to the Description:.<|eot_id|><|start_header_id|>assistant<|end_header_id|> {"Answer" : ["Mental illness","Mental illness--diagnosis","Psychiatric hospital patients","Psychiatric hospitals","Psychiatric hospitals--North Carolina--Raleigh","Psychiatric hospitals--Records"]} <|eot_id|> | Here is the Description of a dataset. Description:'This dataset was transcribed from photos of the original, handwritten admissions ledgers for the North Carolina Asylum for the Insane (later known as Dorothea Dix Hospital) held at the State Archives of North Carolina. The original records are publicly available under the North Carolina Public Records Act, which indicates that records created by state government entities more than 100 years ago are publicly accessible through the State Archives of North Carolina. Historical finding aid at the State Archives of North Carolina (1977) notes that admissions ledger was maintained from the opening of the hospital in 1856 to 1937 (Vol. 1: 1856-1911; Vol. 2: 1911-1929; Vol. 3: 1929-1937). For the period relevant here (1856-1920), this was a hand-written ledger recording both the admission (with identifying admissions number) and disposition (di' . Please return only a json list of at most 3 Keywords corresponding to the Description:. | This dataset was transcribed from photos of the original, handwritten admissions ledgers for the North Carolina Asylum for the Insane (later known as Dorothea Dix Hospital) held at the State Archives of North Carolina. The original records are publicly available under the North Carolina Public Records Act, which indicates that records created by state government entities more than 100 years ago are publicly accessible through the State Archives of North Carolina. Historical finding aid at the State Archives of North Carolina (1977) notes that admissions ledger was maintained from the opening of the hospital in 1856 to 1937 (Vol. 1: 1856-1911; Vol. 2: 1911-1929; Vol. 3: 1929-1937). For the period relevant here (1856-1920), this was a hand-written ledger recording both the admission (with identifying admissions number) and disposition (di | Arts and Humanities | Mental illness; Mental illness--diagnosis; Psychiatric hospital patients; Psychiatric hospitals; Psychiatric hospitals--North Carolina--Raleigh; Psychiatric hospitals--Records |
doi:10.15139/S3/LNTB9R | Dorothea Dix Hospital Admissions Ledger Dataset, Patients 0000-7827 | <|begin_of_text|><|start_header_id|>system<|end_header_id|> You are a research archivist expert in dataset metadata. Answer the question truthfully. <|eot_id|><|start_header_id|>user<|end_header_id|> Here is the Description of a dataset. Description:'This dataset was transcribed from photos of the original, handwritten admissions ledgers for the North Carolina Asylum for the Insane (later known as Dorothea Dix Hospital) held at the State Archives of North Carolina. The original records are publicly available under the North Carolina Public Records Act, which indicates that records created by state government entities more than 100 years ago are publicly accessible through the State Archives of North Carolina. Historical finding aid at the State Archives of North Carolina (1977) notes that admissions ledger was maintained from the opening of the hospital in 1856 to 1937 (Vol. 1: 1856-1911; Vol. 2: 1911-1929; Vol. 3: 1929-1937). For the period relevant here (1856-1920), this was a hand-written ledger recording both the admission (with identifying admissions number) and disposition (di' . Please return only a json list of at most 3 Keywords corresponding to the Description:.<|eot_id|><|start_header_id|>assistant<|end_header_id|> {"Answer" : ["Mental illness","Mental illness--diagnosis","Psychiatric hospital patients","Psychiatric hospitals","Psychiatric hospitals--North Carolina--Raleigh","Psychiatric hospitals--Records"]} <|eot_id|> | Here is the Description of a dataset. Description:'This dataset was transcribed from photos of the original, handwritten admissions ledgers for the North Carolina Asylum for the Insane (later known as Dorothea Dix Hospital) held at the State Archives of North Carolina. The original records are publicly available under the North Carolina Public Records Act, which indicates that records created by state government entities more than 100 years ago are publicly accessible through the State Archives of North Carolina. Historical finding aid at the State Archives of North Carolina (1977) notes that admissions ledger was maintained from the opening of the hospital in 1856 to 1937 (Vol. 1: 1856-1911; Vol. 2: 1911-1929; Vol. 3: 1929-1937). For the period relevant here (1856-1920), this was a hand-written ledger recording both the admission (with identifying admissions number) and disposition (di' . Please return only a json list of at most 3 Keywords corresponding to the Description:. | This dataset was transcribed from photos of the original, handwritten admissions ledgers for the North Carolina Asylum for the Insane (later known as Dorothea Dix Hospital) held at the State Archives of North Carolina. The original records are publicly available under the North Carolina Public Records Act, which indicates that records created by state government entities more than 100 years ago are publicly accessible through the State Archives of North Carolina. Historical finding aid at the State Archives of North Carolina (1977) notes that admissions ledger was maintained from the opening of the hospital in 1856 to 1937 (Vol. 1: 1856-1911; Vol. 2: 1911-1929; Vol. 3: 1929-1937). For the period relevant here (1856-1920), this was a hand-written ledger recording both the admission (with identifying admissions number) and disposition (di | Medicine, Health and Life Sciences | Mental illness; Mental illness--diagnosis; Psychiatric hospital patients; Psychiatric hospitals; Psychiatric hospitals--North Carolina--Raleigh; Psychiatric hospitals--Records |
doi:10.15139/S3/LNTB9R | Dorothea Dix Hospital Admissions Ledger Dataset, Patients 0000-7827 | <|begin_of_text|><|start_header_id|>system<|end_header_id|> You are a research archivist expert in dataset metadata. Answer the question truthfully. <|eot_id|><|start_header_id|>user<|end_header_id|> Here is the Description of a dataset. Description:'This dataset was transcribed from photos of the original, handwritten admissions ledgers for the North Carolina Asylum for the Insane (later known as Dorothea Dix Hospital) held at the State Archives of North Carolina. The original records are publicly available under the North Carolina Public Records Act, which indicates that records created by state government entities more than 100 years ago are publicly accessible through the State Archives of North Carolina. Historical finding aid at the State Archives of North Carolina (1977) notes that admissions ledger was maintained from the opening of the hospital in 1856 to 1937 (Vol. 1: 1856-1911; Vol. 2: 1911-1929; Vol. 3: 1929-1937). For the period relevant here (1856-1920), this was a hand-written ledger recording both the admission (with identifying admissions number) and disposition (di' . Please return only a json list of at most 3 Keywords corresponding to the Description:.<|eot_id|><|start_header_id|>assistant<|end_header_id|> {"Answer" : ["Mental illness","Mental illness--diagnosis","Psychiatric hospital patients","Psychiatric hospitals","Psychiatric hospitals--North Carolina--Raleigh","Psychiatric hospitals--Records"]} <|eot_id|> | Here is the Description of a dataset. Description:'This dataset was transcribed from photos of the original, handwritten admissions ledgers for the North Carolina Asylum for the Insane (later known as Dorothea Dix Hospital) held at the State Archives of North Carolina. The original records are publicly available under the North Carolina Public Records Act, which indicates that records created by state government entities more than 100 years ago are publicly accessible through the State Archives of North Carolina. Historical finding aid at the State Archives of North Carolina (1977) notes that admissions ledger was maintained from the opening of the hospital in 1856 to 1937 (Vol. 1: 1856-1911; Vol. 2: 1911-1929; Vol. 3: 1929-1937). For the period relevant here (1856-1920), this was a hand-written ledger recording both the admission (with identifying admissions number) and disposition (di' . Please return only a json list of at most 3 Keywords corresponding to the Description:. | This dataset was transcribed from photos of the original, handwritten admissions ledgers for the North Carolina Asylum for the Insane (later known as Dorothea Dix Hospital) held at the State Archives of North Carolina. The original records are publicly available under the North Carolina Public Records Act, which indicates that records created by state government entities more than 100 years ago are publicly accessible through the State Archives of North Carolina. Historical finding aid at the State Archives of North Carolina (1977) notes that admissions ledger was maintained from the opening of the hospital in 1856 to 1937 (Vol. 1: 1856-1911; Vol. 2: 1911-1929; Vol. 3: 1929-1937). For the period relevant here (1856-1920), this was a hand-written ledger recording both the admission (with identifying admissions number) and disposition (di | Social Sciences | Mental illness; Mental illness--diagnosis; Psychiatric hospital patients; Psychiatric hospitals; Psychiatric hospitals--North Carolina--Raleigh; Psychiatric hospitals--Records |
doi:10.15139/S3/M2BCRN | Organizational Network Analysis of AGYW Referrals in Botswana | <|begin_of_text|><|start_header_id|>system<|end_header_id|> You are a research archivist expert in dataset metadata. Answer the question truthfully. <|eot_id|><|start_header_id|>user<|end_header_id|> Here is the Description of a dataset. Description:'The Determined, Resilient, Empowered, AIDS-free, Mentored, and Safe (DREAMS) program, a public-private partnership, is being implemented by the United States Agency for International Development (USAID) in two districts of Botswana to address the structural drivers that increase Adolescent Girls and Young Women's (AGYW) HIV risk, including poverty, gender inequality, GBV, and a lack of education. To support the implementation of DREAMS activities in Gaborone and Kweneng East, USAID contracted Data for Impact (D4I), which is funded by USAID and the United States President’s Emergency Plan for AIDS Relief, to conduct a mixed-methods study in these districts to learn more about referral networks that provide AGYW with DREAMS-related services. D4I conducted an organizational network analysis (ONA) to map the referral network in use by DREAM' . Please return only a json list of at most 3 Keywords corresponding to the Description:.<|eot_id|><|start_header_id|>assistant<|end_header_id|> {"Answer" : ["Dreams, ONA, Organizational Network Analysis, HIV, adolescents, girls, women, gender based violence, GBV"]} <|eot_id|> | Here is the Description of a dataset. Description:'The Determined, Resilient, Empowered, AIDS-free, Mentored, and Safe (DREAMS) program, a public-private partnership, is being implemented by the United States Agency for International Development (USAID) in two districts of Botswana to address the structural drivers that increase Adolescent Girls and Young Women's (AGYW) HIV risk, including poverty, gender inequality, GBV, and a lack of education. To support the implementation of DREAMS activities in Gaborone and Kweneng East, USAID contracted Data for Impact (D4I), which is funded by USAID and the United States President’s Emergency Plan for AIDS Relief, to conduct a mixed-methods study in these districts to learn more about referral networks that provide AGYW with DREAMS-related services. D4I conducted an organizational network analysis (ONA) to map the referral network in use by DREAM' . Please return only a json list of at most 3 Keywords corresponding to the Description:. | The Determined, Resilient, Empowered, AIDS-free, Mentored, and Safe (DREAMS) program, a public-private partnership, is being implemented by the United States Agency for International Development (USAID) in two districts of Botswana to address the structural drivers that increase Adolescent Girls and Young Women's (AGYW) HIV risk, including poverty, gender inequality, GBV, and a lack of education. To support the implementation of DREAMS activities in Gaborone and Kweneng East, USAID contracted Data for Impact (D4I), which is funded by USAID and the United States President’s Emergency Plan for AIDS Relief, to conduct a mixed-methods study in these districts to learn more about referral networks that provide AGYW with DREAMS-related services. D4I conducted an organizational network analysis (ONA) to map the referral network in use by DREAM | Medicine, Health and Life Sciences | Dreams, ONA, Organizational Network Analysis, HIV, adolescents, girls, women, gender based violence, GBV |
doi:10.15139/S3/M2BCRN | Organizational Network Analysis of AGYW Referrals in Botswana | <|begin_of_text|><|start_header_id|>system<|end_header_id|> You are a research archivist expert in dataset metadata. Answer the question truthfully. <|eot_id|><|start_header_id|>user<|end_header_id|> Here is the Description of a dataset. Description:'The Determined, Resilient, Empowered, AIDS-free, Mentored, and Safe (DREAMS) program, a public-private partnership, is being implemented by the United States Agency for International Development (USAID) in two districts of Botswana to address the structural drivers that increase Adolescent Girls and Young Women's (AGYW) HIV risk, including poverty, gender inequality, GBV, and a lack of education. To support the implementation of DREAMS activities in Gaborone and Kweneng East, USAID contracted Data for Impact (D4I), which is funded by USAID and the United States President’s Emergency Plan for AIDS Relief, to conduct a mixed-methods study in these districts to learn more about referral networks that provide AGYW with DREAMS-related services. D4I conducted an organizational network analysis (ONA) to map the referral network in use by DREAM' . Please return only a json list of at most 3 Keywords corresponding to the Description:.<|eot_id|><|start_header_id|>assistant<|end_header_id|> {"Answer" : ["Dreams, ONA, Organizational Network Analysis, HIV, adolescents, girls, women, gender based violence, GBV"]} <|eot_id|> | Here is the Description of a dataset. Description:'The Determined, Resilient, Empowered, AIDS-free, Mentored, and Safe (DREAMS) program, a public-private partnership, is being implemented by the United States Agency for International Development (USAID) in two districts of Botswana to address the structural drivers that increase Adolescent Girls and Young Women's (AGYW) HIV risk, including poverty, gender inequality, GBV, and a lack of education. To support the implementation of DREAMS activities in Gaborone and Kweneng East, USAID contracted Data for Impact (D4I), which is funded by USAID and the United States President’s Emergency Plan for AIDS Relief, to conduct a mixed-methods study in these districts to learn more about referral networks that provide AGYW with DREAMS-related services. D4I conducted an organizational network analysis (ONA) to map the referral network in use by DREAM' . Please return only a json list of at most 3 Keywords corresponding to the Description:. | The Determined, Resilient, Empowered, AIDS-free, Mentored, and Safe (DREAMS) program, a public-private partnership, is being implemented by the United States Agency for International Development (USAID) in two districts of Botswana to address the structural drivers that increase Adolescent Girls and Young Women's (AGYW) HIV risk, including poverty, gender inequality, GBV, and a lack of education. To support the implementation of DREAMS activities in Gaborone and Kweneng East, USAID contracted Data for Impact (D4I), which is funded by USAID and the United States President’s Emergency Plan for AIDS Relief, to conduct a mixed-methods study in these districts to learn more about referral networks that provide AGYW with DREAMS-related services. D4I conducted an organizational network analysis (ONA) to map the referral network in use by DREAM | Social Sciences | Dreams, ONA, Organizational Network Analysis, HIV, adolescents, girls, women, gender based violence, GBV |
doi:10.15139/S3/MLFVKJ | Anna Cameron Kirkland Papers, 1832-1890, and undated | <|begin_of_text|><|start_header_id|>system<|end_header_id|> You are a research archivist expert in dataset metadata. Answer the question truthfully. <|eot_id|><|start_header_id|>user<|end_header_id|> Here is the Description of a dataset. Description:'This artificial collection contains scans and transcriptions of letters by, to, and about Anna Cameron Kirkland (1817-1890) of Hillsborough, North Carolina, who was the first female patient of Dorothea Dix Hospital. More than one hundred relevant letters have been drawn from several different family papers held by the Southern Historical Collection at the University of North Carolina at Chapel Hill Libraries. Although her father died at a relatively young age and was not a wealthy man, Anna was born into one of North Carolina’s most affluent and socially prominent families. Her uncle, Duncan Cameron, owned several plantations in central North Carolina, including Stagville, near Durham, and some 900 slaves. In 1835, she married Alexander Kirkland (1807-1843), son of prominent merchant William Kirkland, who did not inherit his' . Please return only a json list of at most 3 Keywords corresponding to the Description:.<|eot_id|><|start_header_id|>assistant<|end_header_id|> {"Answer" : ["Depression in women","Mental illness","Mental illness--Religious aspects","Mentally ill--Care--North Carolina","Mentally ill women--Care--United States","Psychiatric hospital patients","Psychiatric hospitals--North Carolina--Raleigh","Psychiatric hospitals--Virginia--Staunton","Pyschiatric hospitals","Widowhood--United States--Psychological aspects","Widows"]} <|eot_id|> | Here is the Description of a dataset. Description:'This artificial collection contains scans and transcriptions of letters by, to, and about Anna Cameron Kirkland (1817-1890) of Hillsborough, North Carolina, who was the first female patient of Dorothea Dix Hospital. More than one hundred relevant letters have been drawn from several different family papers held by the Southern Historical Collection at the University of North Carolina at Chapel Hill Libraries. Although her father died at a relatively young age and was not a wealthy man, Anna was born into one of North Carolina’s most affluent and socially prominent families. Her uncle, Duncan Cameron, owned several plantations in central North Carolina, including Stagville, near Durham, and some 900 slaves. In 1835, she married Alexander Kirkland (1807-1843), son of prominent merchant William Kirkland, who did not inherit his' . Please return only a json list of at most 3 Keywords corresponding to the Description:. | This artificial collection contains scans and transcriptions of letters by, to, and about Anna Cameron Kirkland (1817-1890) of Hillsborough, North Carolina, who was the first female patient of Dorothea Dix Hospital. More than one hundred relevant letters have been drawn from several different family papers held by the Southern Historical Collection at the University of North Carolina at Chapel Hill Libraries. Although her father died at a relatively young age and was not a wealthy man, Anna was born into one of North Carolina’s most affluent and socially prominent families. Her uncle, Duncan Cameron, owned several plantations in central North Carolina, including Stagville, near Durham, and some 900 slaves. In 1835, she married Alexander Kirkland (1807-1843), son of prominent merchant William Kirkland, who did not inherit his | Arts and Humanities | Depression in women; Mental illness; Mental illness--Religious aspects; Mentally ill--Care--North Carolina; Mentally ill women--Care--United States; Psychiatric hospital patients; Psychiatric hospitals--North Carolina--Raleigh; Psychiatric hospitals--Virginia--Staunton; Pyschiatric hospitals; Widowhood--United States--Psychological aspects; Widows |
doi:10.15139/S3/MLFVKJ | Anna Cameron Kirkland Papers, 1832-1890, and undated | <|begin_of_text|><|start_header_id|>system<|end_header_id|> You are a research archivist expert in dataset metadata. Answer the question truthfully. <|eot_id|><|start_header_id|>user<|end_header_id|> Here is the Description of a dataset. Description:'This artificial collection contains scans and transcriptions of letters by, to, and about Anna Cameron Kirkland (1817-1890) of Hillsborough, North Carolina, who was the first female patient of Dorothea Dix Hospital. More than one hundred relevant letters have been drawn from several different family papers held by the Southern Historical Collection at the University of North Carolina at Chapel Hill Libraries. Although her father died at a relatively young age and was not a wealthy man, Anna was born into one of North Carolina’s most affluent and socially prominent families. Her uncle, Duncan Cameron, owned several plantations in central North Carolina, including Stagville, near Durham, and some 900 slaves. In 1835, she married Alexander Kirkland (1807-1843), son of prominent merchant William Kirkland, who did not inherit his' . Please return only a json list of at most 3 Keywords corresponding to the Description:.<|eot_id|><|start_header_id|>assistant<|end_header_id|> {"Answer" : ["Depression in women","Mental illness","Mental illness--Religious aspects","Mentally ill--Care--North Carolina","Mentally ill women--Care--United States","Psychiatric hospital patients","Psychiatric hospitals--North Carolina--Raleigh","Psychiatric hospitals--Virginia--Staunton","Pyschiatric hospitals","Widowhood--United States--Psychological aspects","Widows"]} <|eot_id|> | Here is the Description of a dataset. Description:'This artificial collection contains scans and transcriptions of letters by, to, and about Anna Cameron Kirkland (1817-1890) of Hillsborough, North Carolina, who was the first female patient of Dorothea Dix Hospital. More than one hundred relevant letters have been drawn from several different family papers held by the Southern Historical Collection at the University of North Carolina at Chapel Hill Libraries. Although her father died at a relatively young age and was not a wealthy man, Anna was born into one of North Carolina’s most affluent and socially prominent families. Her uncle, Duncan Cameron, owned several plantations in central North Carolina, including Stagville, near Durham, and some 900 slaves. In 1835, she married Alexander Kirkland (1807-1843), son of prominent merchant William Kirkland, who did not inherit his' . Please return only a json list of at most 3 Keywords corresponding to the Description:. | This artificial collection contains scans and transcriptions of letters by, to, and about Anna Cameron Kirkland (1817-1890) of Hillsborough, North Carolina, who was the first female patient of Dorothea Dix Hospital. More than one hundred relevant letters have been drawn from several different family papers held by the Southern Historical Collection at the University of North Carolina at Chapel Hill Libraries. Although her father died at a relatively young age and was not a wealthy man, Anna was born into one of North Carolina’s most affluent and socially prominent families. Her uncle, Duncan Cameron, owned several plantations in central North Carolina, including Stagville, near Durham, and some 900 slaves. In 1835, she married Alexander Kirkland (1807-1843), son of prominent merchant William Kirkland, who did not inherit his | Medicine, Health and Life Sciences | Depression in women; Mental illness; Mental illness--Religious aspects; Mentally ill--Care--North Carolina; Mentally ill women--Care--United States; Psychiatric hospital patients; Psychiatric hospitals--North Carolina--Raleigh; Psychiatric hospitals--Virginia--Staunton; Pyschiatric hospitals; Widowhood--United States--Psychological aspects; Widows |
doi:10.15139/S3/MLFVKJ | Anna Cameron Kirkland Papers, 1832-1890, and undated | <|begin_of_text|><|start_header_id|>system<|end_header_id|> You are a research archivist expert in dataset metadata. Answer the question truthfully. <|eot_id|><|start_header_id|>user<|end_header_id|> Here is the Description of a dataset. Description:'This artificial collection contains scans and transcriptions of letters by, to, and about Anna Cameron Kirkland (1817-1890) of Hillsborough, North Carolina, who was the first female patient of Dorothea Dix Hospital. More than one hundred relevant letters have been drawn from several different family papers held by the Southern Historical Collection at the University of North Carolina at Chapel Hill Libraries. Although her father died at a relatively young age and was not a wealthy man, Anna was born into one of North Carolina’s most affluent and socially prominent families. Her uncle, Duncan Cameron, owned several plantations in central North Carolina, including Stagville, near Durham, and some 900 slaves. In 1835, she married Alexander Kirkland (1807-1843), son of prominent merchant William Kirkland, who did not inherit his' . Please return only a json list of at most 3 Keywords corresponding to the Description:.<|eot_id|><|start_header_id|>assistant<|end_header_id|> {"Answer" : ["Depression in women","Mental illness","Mental illness--Religious aspects","Mentally ill--Care--North Carolina","Mentally ill women--Care--United States","Psychiatric hospital patients","Psychiatric hospitals--North Carolina--Raleigh","Psychiatric hospitals--Virginia--Staunton","Pyschiatric hospitals","Widowhood--United States--Psychological aspects","Widows"]} <|eot_id|> | Here is the Description of a dataset. Description:'This artificial collection contains scans and transcriptions of letters by, to, and about Anna Cameron Kirkland (1817-1890) of Hillsborough, North Carolina, who was the first female patient of Dorothea Dix Hospital. More than one hundred relevant letters have been drawn from several different family papers held by the Southern Historical Collection at the University of North Carolina at Chapel Hill Libraries. Although her father died at a relatively young age and was not a wealthy man, Anna was born into one of North Carolina’s most affluent and socially prominent families. Her uncle, Duncan Cameron, owned several plantations in central North Carolina, including Stagville, near Durham, and some 900 slaves. In 1835, she married Alexander Kirkland (1807-1843), son of prominent merchant William Kirkland, who did not inherit his' . Please return only a json list of at most 3 Keywords corresponding to the Description:. | This artificial collection contains scans and transcriptions of letters by, to, and about Anna Cameron Kirkland (1817-1890) of Hillsborough, North Carolina, who was the first female patient of Dorothea Dix Hospital. More than one hundred relevant letters have been drawn from several different family papers held by the Southern Historical Collection at the University of North Carolina at Chapel Hill Libraries. Although her father died at a relatively young age and was not a wealthy man, Anna was born into one of North Carolina’s most affluent and socially prominent families. Her uncle, Duncan Cameron, owned several plantations in central North Carolina, including Stagville, near Durham, and some 900 slaves. In 1835, she married Alexander Kirkland (1807-1843), son of prominent merchant William Kirkland, who did not inherit his | Social Sciences | Depression in women; Mental illness; Mental illness--Religious aspects; Mentally ill--Care--North Carolina; Mentally ill women--Care--United States; Psychiatric hospital patients; Psychiatric hospitals--North Carolina--Raleigh; Psychiatric hospitals--Virginia--Staunton; Pyschiatric hospitals; Widowhood--United States--Psychological aspects; Widows |
doi:10.15139/S3/NP3UW7 | District Mapping Onchocerciasis, Lymphatic Filariasis, and Loiasis in Cameroon | <|begin_of_text|><|start_header_id|>system<|end_header_id|> You are a research archivist expert in dataset metadata. Answer the question truthfully. <|eot_id|><|start_header_id|>user<|end_header_id|> Here is the Description of a dataset. Description:'The goals of the study were to pilot a strategy for mapping and treating onchocerciasis and lymphatic flilariasis (LF) in Loa loa co-endemic areas; to validate the use of the LoaScope in community assessments; and to validate a statistical model calibrated to determine whether community-level prevalence of Loa infection of >20,000 mf/mL is less than 1% in a community by comparing results of the model to results of a community-level random sample prevalence assessment. A community-based cross sectional cluster survey was organized in the Garoua Boulai health district (East Region, Cameroon) where no ivermectin mass administration was ever performed. The prevalence of loiasis was 8.0% (95% CI: 7.2 – 9.0) and was quite different from one cluster to another (Minimum: 0.0%; Maximum: 43.5%). Onchocerciasis was found to be hypo-endemic (rate o' . Please return only a json list of at most 3 Keywords corresponding to the Description:.<|eot_id|><|start_header_id|>assistant<|end_header_id|> {"Answer" : ["Filariasis Test Strip","LoaScope","Loiasis","Lymphatic Filariasis","Onchocerciasis","Ov16 RDT"]} <|eot_id|> | Here is the Description of a dataset. Description:'The goals of the study were to pilot a strategy for mapping and treating onchocerciasis and lymphatic flilariasis (LF) in Loa loa co-endemic areas; to validate the use of the LoaScope in community assessments; and to validate a statistical model calibrated to determine whether community-level prevalence of Loa infection of >20,000 mf/mL is less than 1% in a community by comparing results of the model to results of a community-level random sample prevalence assessment. A community-based cross sectional cluster survey was organized in the Garoua Boulai health district (East Region, Cameroon) where no ivermectin mass administration was ever performed. The prevalence of loiasis was 8.0% (95% CI: 7.2 – 9.0) and was quite different from one cluster to another (Minimum: 0.0%; Maximum: 43.5%). Onchocerciasis was found to be hypo-endemic (rate o' . Please return only a json list of at most 3 Keywords corresponding to the Description:. | The goals of the study were to pilot a strategy for mapping and treating onchocerciasis and lymphatic flilariasis (LF) in Loa loa co-endemic areas; to validate the use of the LoaScope in community assessments; and to validate a statistical model calibrated to determine whether community-level prevalence of Loa infection of >20,000 mf/mL is less than 1% in a community by comparing results of the model to results of a community-level random sample prevalence assessment. A community-based cross sectional cluster survey was organized in the Garoua Boulai health district (East Region, Cameroon) where no ivermectin mass administration was ever performed. The prevalence of loiasis was 8.0% (95% CI: 7.2 – 9.0) and was quite different from one cluster to another (Minimum: 0.0%; Maximum: 43.5%). Onchocerciasis was found to be hypo-endemic (rate o | Medicine, Health and Life Sciences | Filariasis Test Strip; LoaScope; Loiasis; Lymphatic Filariasis; Onchocerciasis; Ov16 RDT |
doi:10.15139/S3/O9FFDU | ECU LGBTQ Health Promotion Team 2016 North Carolina Pride Festival Survey | <|begin_of_text|><|start_header_id|>system<|end_header_id|> You are a research archivist expert in dataset metadata. Answer the question truthfully. <|eot_id|><|start_header_id|>user<|end_header_id|> Here is the Description of a dataset. Description:'BACKGROUND/PURPOSEThis survey gathers data to inform our understanding of workplace discrimination, substance abuse, and health, in relation to lesbian, gay, bisexual, and transgender identity.DESCRIPTION OF PARTICIPANTSAdults attending NC Pride 2016 (a lesbian, gay, bisexual, and transgender community festival open to the public on Duke University's campus on September 24, 2016) in Durham, NC.RESEARCH METHODSWe used iPads to conduct an anonymous survey using convenience sampling with participants at the NC Pride Parade and Festival. The survey took place at the festival portion, which has a sound stage, food vendors, and booths from corporations, businesses, and community organizations. The surveyors requested participation from adults who were walking by the survey team tent, which was rented from NC Pride. Surveyors sta' . Please return only a json list of at most 3 Keywords corresponding to the Description:.<|eot_id|><|start_header_id|>assistant<|end_header_id|> {"Answer" : ["gay","lesbian","sexual minority"]} <|eot_id|> | Here is the Description of a dataset. Description:'BACKGROUND/PURPOSEThis survey gathers data to inform our understanding of workplace discrimination, substance abuse, and health, in relation to lesbian, gay, bisexual, and transgender identity.DESCRIPTION OF PARTICIPANTSAdults attending NC Pride 2016 (a lesbian, gay, bisexual, and transgender community festival open to the public on Duke University's campus on September 24, 2016) in Durham, NC.RESEARCH METHODSWe used iPads to conduct an anonymous survey using convenience sampling with participants at the NC Pride Parade and Festival. The survey took place at the festival portion, which has a sound stage, food vendors, and booths from corporations, businesses, and community organizations. The surveyors requested participation from adults who were walking by the survey team tent, which was rented from NC Pride. Surveyors sta' . Please return only a json list of at most 3 Keywords corresponding to the Description:. | BACKGROUND/PURPOSEThis survey gathers data to inform our understanding of workplace discrimination, substance abuse, and health, in relation to lesbian, gay, bisexual, and transgender identity.DESCRIPTION OF PARTICIPANTSAdults attending NC Pride 2016 (a lesbian, gay, bisexual, and transgender community festival open to the public on Duke University's campus on September 24, 2016) in Durham, NC.RESEARCH METHODSWe used iPads to conduct an anonymous survey using convenience sampling with participants at the NC Pride Parade and Festival. The survey took place at the festival portion, which has a sound stage, food vendors, and booths from corporations, businesses, and community organizations. The surveyors requested participation from adults who were walking by the survey team tent, which was rented from NC Pride. Surveyors sta | Medicine, Health and Life Sciences | gay; lesbian; sexual minority |
doi:10.15139/S3/OGPEJT | Muhuru Bay | <|begin_of_text|><|start_header_id|>system<|end_header_id|> You are a research archivist expert in dataset metadata. Answer the question truthfully. <|eot_id|><|start_header_id|>user<|end_header_id|> Here is the Description of a dataset. Description:'The 'Multi-Level HIV Prevention in Rural Kenya: Addressing the Individual and Setting-Level Factors Contributing to HIV Among Youth' study was conducted in 2008 in Muhuru Bay, Kenya. Data were collected on HIV risk factors and various mental health measures, including the SDQ, CDI, RBG, PTSD Reaction Index for Children/Adolescents, and an adaptation of the Things I Have Seen and Heard Scale. The study population is comprised of 325 adolescents and their legal guardians. Adolescents were randomly selected from among students enrolled in Standards 5-8 in the 14 schools (9 public, 5 private) in the Muhuru Division of Nyanza, Kenya. Adolescent participants were between the ages of 9 and 18. A caregiver for each enrolled adolescent participant also participated in the study. Both adolescent and caregiver participants completed a' . Please return only a json list of at most 3 Keywords corresponding to the Description:.<|eot_id|><|start_header_id|>assistant<|end_header_id|> {"Answer" : ["CDI","PTSD Reaction Index for Children/Adolescents","RBG","SDQ","Things I Have Seen and Heard Scale"]} <|eot_id|> | Here is the Description of a dataset. Description:'The 'Multi-Level HIV Prevention in Rural Kenya: Addressing the Individual and Setting-Level Factors Contributing to HIV Among Youth' study was conducted in 2008 in Muhuru Bay, Kenya. Data were collected on HIV risk factors and various mental health measures, including the SDQ, CDI, RBG, PTSD Reaction Index for Children/Adolescents, and an adaptation of the Things I Have Seen and Heard Scale. The study population is comprised of 325 adolescents and their legal guardians. Adolescents were randomly selected from among students enrolled in Standards 5-8 in the 14 schools (9 public, 5 private) in the Muhuru Division of Nyanza, Kenya. Adolescent participants were between the ages of 9 and 18. A caregiver for each enrolled adolescent participant also participated in the study. Both adolescent and caregiver participants completed a' . Please return only a json list of at most 3 Keywords corresponding to the Description:. | The 'Multi-Level HIV Prevention in Rural Kenya: Addressing the Individual and Setting-Level Factors Contributing to HIV Among Youth' study was conducted in 2008 in Muhuru Bay, Kenya. Data were collected on HIV risk factors and various mental health measures, including the SDQ, CDI, RBG, PTSD Reaction Index for Children/Adolescents, and an adaptation of the Things I Have Seen and Heard Scale. The study population is comprised of 325 adolescents and their legal guardians. Adolescents were randomly selected from among students enrolled in Standards 5-8 in the 14 schools (9 public, 5 private) in the Muhuru Division of Nyanza, Kenya. Adolescent participants were between the ages of 9 and 18. A caregiver for each enrolled adolescent participant also participated in the study. Both adolescent and caregiver participants completed a | Medicine, Health and Life Sciences | CDI; PTSD Reaction Index for Children/Adolescents; RBG; SDQ; Things I Have Seen and Heard Scale |
doi:10.15139/S3/P8RKKG | Improving Nutrition through Community-based Approaches (INCA) Activity Baseline Survey 2017 | <|begin_of_text|><|start_header_id|>system<|end_header_id|> You are a research archivist expert in dataset metadata. Answer the question truthfully. <|eot_id|><|start_header_id|>user<|end_header_id|> Here is the Description of a dataset. Description:'The 2017 INCA Baseline Evaluation Survey provides household- and individual-level data for the evaluation of the USAID/Bangladesh’ Improving Nutrition through Community-based Approaches (INCA) activity. The survey collected information on nutritional status, knowledge and practices related to nutrition, and on utilization of nutrition and health services from a representative sample of target households and women and children under age 2 in INCA project areas. The survey also included a group of households from adjacent non-project areas' . Please return only a json list of at most 3 Keywords corresponding to the Description:.<|eot_id|><|start_header_id|>assistant<|end_header_id|> {"Answer" : ["Bangladesh","Maternal and child health service","Nutritional status","Nutrition knowledge and practice"]} <|eot_id|> | Here is the Description of a dataset. Description:'The 2017 INCA Baseline Evaluation Survey provides household- and individual-level data for the evaluation of the USAID/Bangladesh’ Improving Nutrition through Community-based Approaches (INCA) activity. The survey collected information on nutritional status, knowledge and practices related to nutrition, and on utilization of nutrition and health services from a representative sample of target households and women and children under age 2 in INCA project areas. The survey also included a group of households from adjacent non-project areas' . Please return only a json list of at most 3 Keywords corresponding to the Description:. | The 2017 INCA Baseline Evaluation Survey provides household- and individual-level data for the evaluation of the USAID/Bangladesh’ Improving Nutrition through Community-based Approaches (INCA) activity. The survey collected information on nutritional status, knowledge and practices related to nutrition, and on utilization of nutrition and health services from a representative sample of target households and women and children under age 2 in INCA project areas. The survey also included a group of households from adjacent non-project areas | Medicine, Health and Life Sciences | Bangladesh; Maternal and child health service; Nutritional status; Nutrition knowledge and practice |
doi:10.15139/S3/P8RKKG | Improving Nutrition through Community-based Approaches (INCA) Activity Baseline Survey 2017 | <|begin_of_text|><|start_header_id|>system<|end_header_id|> You are a research archivist expert in dataset metadata. Answer the question truthfully. <|eot_id|><|start_header_id|>user<|end_header_id|> Here is the Description of a dataset. Description:'The 2017 INCA Baseline Evaluation Survey provides household- and individual-level data for the evaluation of the USAID/Bangladesh’ Improving Nutrition through Community-based Approaches (INCA) activity. The survey collected information on nutritional status, knowledge and practices related to nutrition, and on utilization of nutrition and health services from a representative sample of target households and women and children under age 2 in INCA project areas. The survey also included a group of households from adjacent non-project areas' . Please return only a json list of at most 3 Keywords corresponding to the Description:.<|eot_id|><|start_header_id|>assistant<|end_header_id|> {"Answer" : ["Bangladesh","Maternal and child health service","Nutritional status","Nutrition knowledge and practice"]} <|eot_id|> | Here is the Description of a dataset. Description:'The 2017 INCA Baseline Evaluation Survey provides household- and individual-level data for the evaluation of the USAID/Bangladesh’ Improving Nutrition through Community-based Approaches (INCA) activity. The survey collected information on nutritional status, knowledge and practices related to nutrition, and on utilization of nutrition and health services from a representative sample of target households and women and children under age 2 in INCA project areas. The survey also included a group of households from adjacent non-project areas' . Please return only a json list of at most 3 Keywords corresponding to the Description:. | The 2017 INCA Baseline Evaluation Survey provides household- and individual-level data for the evaluation of the USAID/Bangladesh’ Improving Nutrition through Community-based Approaches (INCA) activity. The survey collected information on nutritional status, knowledge and practices related to nutrition, and on utilization of nutrition and health services from a representative sample of target households and women and children under age 2 in INCA project areas. The survey also included a group of households from adjacent non-project areas | Social Sciences | Bangladesh; Maternal and child health service; Nutritional status; Nutrition knowledge and practice |
doi:10.15139/S3/PIJJGC | A Study of the Local Capacity Initiative in Uganda: Longitudinal Survey of Civil Society Organizations | <|begin_of_text|><|start_header_id|>system<|end_header_id|> You are a research archivist expert in dataset metadata. Answer the question truthfully. <|eot_id|><|start_header_id|>user<|end_header_id|> Here is the Description of a dataset. Description:'The primary purpose of the Local Capacity Initiative (LCI) evaluation, including the Uganda case study, was to foster learning about how policy advocacy activities can contribute to increased access to quality HIV services for key populations and vulnerable groups. Baseline and endline surveys were conducted with staff from 15 participating civil society organizations (CSOs). The survey measured skill transfer as a result of various trainings (strategic planning, legal and policy audit, use of community score cards) including knowledge in these areas, self-efficacy to conduct related activities, and actual participation in policy advocacy activities' . Please return only a json list of at most 3 Keywords corresponding to the Description:.<|eot_id|><|start_header_id|>assistant<|end_header_id|> {"Answer" : ["Civil society organizations","CSOs","HIV","Key populations","Uganda","Vulnerable groups"]} <|eot_id|> | Here is the Description of a dataset. Description:'The primary purpose of the Local Capacity Initiative (LCI) evaluation, including the Uganda case study, was to foster learning about how policy advocacy activities can contribute to increased access to quality HIV services for key populations and vulnerable groups. Baseline and endline surveys were conducted with staff from 15 participating civil society organizations (CSOs). The survey measured skill transfer as a result of various trainings (strategic planning, legal and policy audit, use of community score cards) including knowledge in these areas, self-efficacy to conduct related activities, and actual participation in policy advocacy activities' . Please return only a json list of at most 3 Keywords corresponding to the Description:. | The primary purpose of the Local Capacity Initiative (LCI) evaluation, including the Uganda case study, was to foster learning about how policy advocacy activities can contribute to increased access to quality HIV services for key populations and vulnerable groups. Baseline and endline surveys were conducted with staff from 15 participating civil society organizations (CSOs). The survey measured skill transfer as a result of various trainings (strategic planning, legal and policy audit, use of community score cards) including knowledge in these areas, self-efficacy to conduct related activities, and actual participation in policy advocacy activities | Medicine, Health and Life Sciences | Civil society organizations; CSOs; HIV; Key populations; Uganda; Vulnerable groups |
doi:10.15139/S3/PMAAWG | CHAMPS Limited Dataset, v4.2 | <|begin_of_text|><|start_header_id|>system<|end_header_id|> You are a research archivist expert in dataset metadata. Answer the question truthfully. <|eot_id|><|start_header_id|>user<|end_header_id|> Here is the Description of a dataset. Description:'(rev. 2021-04-01) Request dataset here: https://champshealth.org/data-access/ Version 4.2 of the standard, limited CHAMPS dataset included these files: case demographics (including MITS measurements), verbal autopsy, DeCoDe results, TAC results, and lab results. Sixteen new columns were added to this dataset; one column was renamed. This dataset is updated monthly. The version of this dataset changes quarterly when a revised ICD-10 mapping document is uploaded.</br' . Please return only a json list of at most 3 Keywords corresponding to the Description:.<|eot_id|><|start_header_id|>assistant<|end_header_id|> {"Answer" : ["Anemias","Assays: Bordatella spp., C. difficile, C. diphtheria, H. influenzae, Arenavirus/Lassa Fever, MERS coronavirus, Salmonella spp., V. cholerae, Acinetobacter baumannii, Adenovirus, Adenovirus 40/41, Aeromonas spp., Ascaris lumbricoides, Astrovirus, Bartonella spp.","Bordetella parapertussi, Bordetella bronchiseptica","Bordetella pertussis, Bordetella holmseii","Bordetella pertussis (pertussis toxin), Brucellaspp., Burkholderia pseudomallei, C. difficile paLOC, C. difficile tcdA, C. difficile tcdB, Campylobacter coli, Campylobacter jejuni, Candida albicans, Crimean-Congo Hemorrhagic Fever virus (CCHF), Chikungunya virus, Chlamydia pneumoniae, Chlamydia trachomatis, Corynebacterium diptheriae","Corynebacterium ulcerans, Corynebacterium pseudotuberculosis","Corynebactrium spp. (tox gene), Coxiella burnettii","Cryptococcus neoformans, Cryptococcus gattii","Cryptosporidium parvum, Cytomegalovirus (CMV), Dengue (pan), Entamoeba histolytica, Escherichia coli (aaiC gene), Escherichia coli (aatA gene), Enterococcus facium, Enterococcus faecalis, Enterovirus, Escherichia coli (bfpA gene), Escherichia coli (eae gene), Escherichia coli/Shigella, Escherichia coli (heat-labile enterotoxin), Escherichia coli (heat-stable enterotoxin)","Bacterial Infections and Mycoses","Birth Trauma","Cancer","Cardiovascular Diseases","Cervical Insufficiency and Pelvic Anomalies","Cesarean Delivery","Chemically-Induced Disorders","Chorioamnionitis and Membrane Complications","Congenital Birth Defects","Congenital, Hereditary, and Neonatal Diseases and Abnormalities","Congenital Infection","Diarrheal Diseases","Digestive System Diseases","Disorders of Environmental Origin","Endocrine System Diseases","Epilepsy","Eye Diseases","Female Urogenital Diseases and Pregnancy Complications","Giardia spp, Group A Streptococcus, Group B Streptococcus, Haemophilus influenzae, Haemophilus influenzae type B, Human coronavirus 1 (229E), Human coronavirus 2 (NL63), Human coronavirus 3 (OC43), Human coronavirus 4 (HKU1), Hepatitis E virus, Human metapneumovirus (HMPV), Herpes simplex virus 1 (HSV1), Herpes simplex virus 2 (HSV2), Human nucleic acid control (Rnase P), Influenza A, Influenza B, Internal Positive Control (IPC), Japanese encephalitis virus, Klebsiella pneumoniae","PAN Lassa Fever Virus, can cross react with other arenavirus","Lassa Fever Virus target 1 and target 2, Leptospira (pan-serovar), Listeria monocytogenes, Measles, MERS coronavirus (N gene), MERS coronavirus (upE gene), Moraxella catarrhalis, Mumps, MS2 phage for extraction control, Mycobacterium tuberculosis, Mycoplasma pneumoniae, Neisseria gonorrhoeae, Neisseria meningitidis, Nipah virus, Norovirus GI, Norovirus GII, Orientia tsutsugamushi, Parechovirus, Parvovirus B19 VP2","Parainfluenza virus type 1, type 2, type 3 and type 4","Plasmodium falciparum, Plasmodium vivax, Pneumocystis jirovecii, Pseudomonas aeruginosa, Respiratory syncytical virus (RSV), Rhinovirus, Rickettsia spp., Rift Valley Fever, Rotavirus A, Rotavirus B, Rotavirus C","Global Health","Heart Diseases","Hemic and Lymphatic Diseases","HIV","Immune System Disease","Injury","Kidney Disease","Liver Disease","Lower Respiratory Infections","Malaria","Malnutrition","Malpresentation Before Labor","Maternal Circulatory and Respiratory Diseases","Maternal Diabetes","Maternal HIV","Maternal Hypertension","Maternal Infection","Maternal Injury and Accident","Maternal Medication or Toxic Exposure","Maternal Nutritional Disorder","Maternal Surgical and Medical Procedures","Measles","Meningitis/Encephalitis","Motor Neuron Disease","Multiple Gestation","Musculoskeletal Diseases","Neonatal Aspiration Syndromes","Neonatal Encephalopathy","Neonatal Preterm Birth Complications","Neonatal Sepsis","Neoplasms","Nervous System Diseases","Nutritional and Metabolic Diseases","Obstructed Labor and Fetal Malpresentation","Other Disorders of Fluid, Electrolyte and Acid-Base Balance","Other Endocrine, Metabolic, Blood and Immune Disorders","Other Gastrointestinal Disease","Other Immunodeficiencies","Other Infections","Other Injury","Other Labor and Delivery Complications","Other Maternal Factor","Other Neonatal Disorders","Other Neurological Disorders","Other Nutritional Deficiencies","Other Respiratory Diseases","Other Skin and Subcutaneous Diseases","Paralytic Ileus and Intestinal Obstruction","Parasitic Diseases","Pathological Conditions, Signs and Symptoms","Perinatal Asphyxia/Hypoxia","Placental Complications","Poisoning","Premature Rupture of Membranes","Preterm Labor or Delivery","Prolapsed Cord","Public Health","Respiratory Tract Diseases","Road Injuries","Sepsis","Sickle Cell Disorders","Skin and Connective Tissue Diseases","Spontaneous Abortion","Stomatognathic Diseases","Sudden Infant Death Syndrome (SIDS)","Syphilis","Tuberculosis (TB)","Umbilical Cord Complications","Upper Respiratory Infections","Uterine Fluid Disorders","Uterine Rupture","Virus Diseases","Wounds and Injuries"]} <|eot_id|> | Here is the Description of a dataset. Description:'(rev. 2021-04-01) Request dataset here: https://champshealth.org/data-access/ Version 4.2 of the standard, limited CHAMPS dataset included these files: case demographics (including MITS measurements), verbal autopsy, DeCoDe results, TAC results, and lab results. Sixteen new columns were added to this dataset; one column was renamed. This dataset is updated monthly. The version of this dataset changes quarterly when a revised ICD-10 mapping document is uploaded.</br' . Please return only a json list of at most 3 Keywords corresponding to the Description:. | (rev. 2021-04-01) Request dataset here: https://champshealth.org/data-access/ Version 4.2 of the standard, limited CHAMPS dataset included these files: case demographics (including MITS measurements), verbal autopsy, DeCoDe results, TAC results, and lab results. Sixteen new columns were added to this dataset; one column was renamed. This dataset is updated monthly. The version of this dataset changes quarterly when a revised ICD-10 mapping document is uploaded.</br | Medicine, Health and Life Sciences | Anemias; Assays: Bordatella spp., C. difficile, C. diphtheria, H. influenzae, Arenavirus/Lassa Fever, MERS coronavirus, Salmonella spp., V. cholerae, Acinetobacter baumannii, Adenovirus, Adenovirus 40/41, Aeromonas spp., Ascaris lumbricoides, Astrovirus, Bartonella spp.; Bordetella parapertussi, Bordetella bronchiseptica; Bordetella pertussis, Bordetella holmseii; Bordetella pertussis (pertussis toxin), Brucellaspp., Burkholderia pseudomallei, C. difficile paLOC, C. difficile tcdA, C. difficile tcdB, Campylobacter coli, Campylobacter jejuni, Candida albicans, Crimean-Congo Hemorrhagic Fever virus (CCHF), Chikungunya virus, Chlamydia pneumoniae, Chlamydia trachomatis, Corynebacterium diptheriae; Corynebacterium ulcerans, Corynebacterium pseudotuberculosis; Corynebactrium spp. (tox gene), Coxiella burnettii; Cryptococcus neoformans, Cryptococcus gattii; Cryptosporidium parvum, Cytomegalovirus (CMV), Dengue (pan), Entamoeba histolytica, Escherichia coli (aaiC gene), Escherichia coli (aatA gene), Enterococcus facium, Enterococcus faecalis, Enterovirus, Escherichia coli (bfpA gene), Escherichia coli (eae gene), Escherichia coli/Shigella, Escherichia coli (heat-labile enterotoxin), Escherichia coli (heat-stable enterotoxin); Bacterial Infections and Mycoses; Birth Trauma; Cancer; Cardiovascular Diseases; Cervical Insufficiency and Pelvic Anomalies; Cesarean Delivery; Chemically-Induced Disorders; Chorioamnionitis and Membrane Complications; Congenital Birth Defects; Congenital, Hereditary, and Neonatal Diseases and Abnormalities; Congenital Infection; Diarrheal Diseases; Digestive System Diseases; Disorders of Environmental Origin; Endocrine System Diseases; Epilepsy; Eye Diseases; Female Urogenital Diseases and Pregnancy Complications; Giardia spp, Group A Streptococcus, Group B Streptococcus, Haemophilus influenzae, Haemophilus influenzae type B, Human coronavirus 1 (229E), Human coronavirus 2 (NL63), Human coronavirus 3 (OC43), Human coronavirus 4 (HKU1), Hepatitis E virus, Human metapneumovirus (HMPV), Herpes simplex virus 1 (HSV1), Herpes simplex virus 2 (HSV2), Human nucleic acid control (Rnase P), Influenza A, Influenza B, Internal Positive Control (IPC), Japanese encephalitis virus, Klebsiella pneumoniae; PAN Lassa Fever Virus, can cross react with other arenavirus; Lassa Fever Virus target 1 and target 2, Leptospira (pan-serovar), Listeria monocytogenes, Measles, MERS coronavirus (N gene), MERS coronavirus (upE gene), Moraxella catarrhalis, Mumps, MS2 phage for extraction control, Mycobacterium tuberculosis, Mycoplasma pneumoniae, Neisseria gonorrhoeae, Neisseria meningitidis, Nipah virus, Norovirus GI, Norovirus GII, Orientia tsutsugamushi, Parechovirus, Parvovirus B19 VP2; Parainfluenza virus type 1, type 2, type 3 and type 4; Plasmodium falciparum, Plasmodium vivax, Pneumocystis jirovecii, Pseudomonas aeruginosa, Respiratory syncytical virus (RSV), Rhinovirus, Rickettsia spp., Rift Valley Fever, Rotavirus A, Rotavirus B, Rotavirus C; Global Health; Heart Diseases; Hemic and Lymphatic Diseases; HIV; Immune System Disease; Injury; Kidney Disease; Liver Disease; Lower Respiratory Infections; Malaria; Malnutrition; Malpresentation Before Labor; Maternal Circulatory and Respiratory Diseases; Maternal Diabetes; Maternal HIV; Maternal Hypertension; Maternal Infection; Maternal Injury and Accident; Maternal Medication or Toxic Exposure; Maternal Nutritional Disorder; Maternal Surgical and Medical Procedures; Measles; Meningitis/Encephalitis; Motor Neuron Disease; Multiple Gestation; Musculoskeletal Diseases; Neonatal Aspiration Syndromes; Neonatal Encephalopathy; Neonatal Preterm Birth Complications; Neonatal Sepsis; Neoplasms; Nervous System Diseases; Nutritional and Metabolic Diseases; Obstructed Labor and Fetal Malpresentation; Other Disorders of Fluid, Electrolyte and Acid-Base Balance; Other Endocrine, Metabolic, Blood and Immune Disorders; Other Gastrointestinal Disease; Other Immunodeficiencies; Other Infections; Other Injury; Other Labor and Delivery Complications; Other Maternal Factor; Other Neonatal Disorders; Other Neurological Disorders; Other Nutritional Deficiencies; Other Respiratory Diseases; Other Skin and Subcutaneous Diseases; Paralytic Ileus and Intestinal Obstruction; Parasitic Diseases; Pathological Conditions, Signs and Symptoms; Perinatal Asphyxia/Hypoxia; Placental Complications; Poisoning; Premature Rupture of Membranes; Preterm Labor or Delivery; Prolapsed Cord; Public Health; Respiratory Tract Diseases; Road Injuries; Sepsis; Sickle Cell Disorders; Skin and Connective Tissue Diseases; Spontaneous Abortion; Stomatognathic Diseases; Sudden Infant Death Syndrome (SIDS); Syphilis; Tuberculosis (TB); Umbilical Cord Complications; Upper Respiratory Infections; Uterine Fluid Disorders; Uterine Rupture; Virus Diseases; Wounds and Injuries |
doi:10.15139/S3/PMAAWG | CHAMPS Limited Dataset, v4.2 | <|begin_of_text|><|start_header_id|>system<|end_header_id|> You are a research archivist expert in dataset metadata. Answer the question truthfully. <|eot_id|><|start_header_id|>user<|end_header_id|> Here is the Description of a dataset. Description:'(rev. 2021-04-01) Request dataset here: https://champshealth.org/data-access/ Version 4.2 of the standard, limited CHAMPS dataset included these files: case demographics (including MITS measurements), verbal autopsy, DeCoDe results, TAC results, and lab results. Sixteen new columns were added to this dataset; one column was renamed. This dataset is updated monthly. The version of this dataset changes quarterly when a revised ICD-10 mapping document is uploaded.</br' . Please return only a json list of at most 3 Keywords corresponding to the Description:.<|eot_id|><|start_header_id|>assistant<|end_header_id|> {"Answer" : ["Anemias","Assays: Bordatella spp., C. difficile, C. diphtheria, H. influenzae, Arenavirus/Lassa Fever, MERS coronavirus, Salmonella spp., V. cholerae, Acinetobacter baumannii, Adenovirus, Adenovirus 40/41, Aeromonas spp., Ascaris lumbricoides, Astrovirus, Bartonella spp.","Bordetella parapertussi, Bordetella bronchiseptica","Bordetella pertussis, Bordetella holmseii","Bordetella pertussis (pertussis toxin), Brucellaspp., Burkholderia pseudomallei, C. difficile paLOC, C. difficile tcdA, C. difficile tcdB, Campylobacter coli, Campylobacter jejuni, Candida albicans, Crimean-Congo Hemorrhagic Fever virus (CCHF), Chikungunya virus, Chlamydia pneumoniae, Chlamydia trachomatis, Corynebacterium diptheriae","Corynebacterium ulcerans, Corynebacterium pseudotuberculosis","Corynebactrium spp. (tox gene), Coxiella burnettii","Cryptococcus neoformans, Cryptococcus gattii","Cryptosporidium parvum, Cytomegalovirus (CMV), Dengue (pan), Entamoeba histolytica, Escherichia coli (aaiC gene), Escherichia coli (aatA gene), Enterococcus facium, Enterococcus faecalis, Enterovirus, Escherichia coli (bfpA gene), Escherichia coli (eae gene), Escherichia coli/Shigella, Escherichia coli (heat-labile enterotoxin), Escherichia coli (heat-stable enterotoxin)","Bacterial Infections and Mycoses","Birth Trauma","Cancer","Cardiovascular Diseases","Cervical Insufficiency and Pelvic Anomalies","Cesarean Delivery","Chemically-Induced Disorders","Chorioamnionitis and Membrane Complications","Congenital Birth Defects","Congenital, Hereditary, and Neonatal Diseases and Abnormalities","Congenital Infection","Diarrheal Diseases","Digestive System Diseases","Disorders of Environmental Origin","Endocrine System Diseases","Epilepsy","Eye Diseases","Female Urogenital Diseases and Pregnancy Complications","Giardia spp, Group A Streptococcus, Group B Streptococcus, Haemophilus influenzae, Haemophilus influenzae type B, Human coronavirus 1 (229E), Human coronavirus 2 (NL63), Human coronavirus 3 (OC43), Human coronavirus 4 (HKU1), Hepatitis E virus, Human metapneumovirus (HMPV), Herpes simplex virus 1 (HSV1), Herpes simplex virus 2 (HSV2), Human nucleic acid control (Rnase P), Influenza A, Influenza B, Internal Positive Control (IPC), Japanese encephalitis virus, Klebsiella pneumoniae","PAN Lassa Fever Virus, can cross react with other arenavirus","Lassa Fever Virus target 1 and target 2, Leptospira (pan-serovar), Listeria monocytogenes, Measles, MERS coronavirus (N gene), MERS coronavirus (upE gene), Moraxella catarrhalis, Mumps, MS2 phage for extraction control, Mycobacterium tuberculosis, Mycoplasma pneumoniae, Neisseria gonorrhoeae, Neisseria meningitidis, Nipah virus, Norovirus GI, Norovirus GII, Orientia tsutsugamushi, Parechovirus, Parvovirus B19 VP2","Parainfluenza virus type 1, type 2, type 3 and type 4","Plasmodium falciparum, Plasmodium vivax, Pneumocystis jirovecii, Pseudomonas aeruginosa, Respiratory syncytical virus (RSV), Rhinovirus, Rickettsia spp., Rift Valley Fever, Rotavirus A, Rotavirus B, Rotavirus C","Global Health","Heart Diseases","Hemic and Lymphatic Diseases","HIV","Immune System Disease","Injury","Kidney Disease","Liver Disease","Lower Respiratory Infections","Malaria","Malnutrition","Malpresentation Before Labor","Maternal Circulatory and Respiratory Diseases","Maternal Diabetes","Maternal HIV","Maternal Hypertension","Maternal Infection","Maternal Injury and Accident","Maternal Medication or Toxic Exposure","Maternal Nutritional Disorder","Maternal Surgical and Medical Procedures","Measles","Meningitis/Encephalitis","Motor Neuron Disease","Multiple Gestation","Musculoskeletal Diseases","Neonatal Aspiration Syndromes","Neonatal Encephalopathy","Neonatal Preterm Birth Complications","Neonatal Sepsis","Neoplasms","Nervous System Diseases","Nutritional and Metabolic Diseases","Obstructed Labor and Fetal Malpresentation","Other Disorders of Fluid, Electrolyte and Acid-Base Balance","Other Endocrine, Metabolic, Blood and Immune Disorders","Other Gastrointestinal Disease","Other Immunodeficiencies","Other Infections","Other Injury","Other Labor and Delivery Complications","Other Maternal Factor","Other Neonatal Disorders","Other Neurological Disorders","Other Nutritional Deficiencies","Other Respiratory Diseases","Other Skin and Subcutaneous Diseases","Paralytic Ileus and Intestinal Obstruction","Parasitic Diseases","Pathological Conditions, Signs and Symptoms","Perinatal Asphyxia/Hypoxia","Placental Complications","Poisoning","Premature Rupture of Membranes","Preterm Labor or Delivery","Prolapsed Cord","Public Health","Respiratory Tract Diseases","Road Injuries","Sepsis","Sickle Cell Disorders","Skin and Connective Tissue Diseases","Spontaneous Abortion","Stomatognathic Diseases","Sudden Infant Death Syndrome (SIDS)","Syphilis","Tuberculosis (TB)","Umbilical Cord Complications","Upper Respiratory Infections","Uterine Fluid Disorders","Uterine Rupture","Virus Diseases","Wounds and Injuries"]} <|eot_id|> | Here is the Description of a dataset. Description:'(rev. 2021-04-01) Request dataset here: https://champshealth.org/data-access/ Version 4.2 of the standard, limited CHAMPS dataset included these files: case demographics (including MITS measurements), verbal autopsy, DeCoDe results, TAC results, and lab results. Sixteen new columns were added to this dataset; one column was renamed. This dataset is updated monthly. The version of this dataset changes quarterly when a revised ICD-10 mapping document is uploaded.</br' . Please return only a json list of at most 3 Keywords corresponding to the Description:. | (rev. 2021-04-01) Request dataset here: https://champshealth.org/data-access/ Version 4.2 of the standard, limited CHAMPS dataset included these files: case demographics (including MITS measurements), verbal autopsy, DeCoDe results, TAC results, and lab results. Sixteen new columns were added to this dataset; one column was renamed. This dataset is updated monthly. The version of this dataset changes quarterly when a revised ICD-10 mapping document is uploaded.</br | Other | Anemias; Assays: Bordatella spp., C. difficile, C. diphtheria, H. influenzae, Arenavirus/Lassa Fever, MERS coronavirus, Salmonella spp., V. cholerae, Acinetobacter baumannii, Adenovirus, Adenovirus 40/41, Aeromonas spp., Ascaris lumbricoides, Astrovirus, Bartonella spp.; Bordetella parapertussi, Bordetella bronchiseptica; Bordetella pertussis, Bordetella holmseii; Bordetella pertussis (pertussis toxin), Brucellaspp., Burkholderia pseudomallei, C. difficile paLOC, C. difficile tcdA, C. difficile tcdB, Campylobacter coli, Campylobacter jejuni, Candida albicans, Crimean-Congo Hemorrhagic Fever virus (CCHF), Chikungunya virus, Chlamydia pneumoniae, Chlamydia trachomatis, Corynebacterium diptheriae; Corynebacterium ulcerans, Corynebacterium pseudotuberculosis; Corynebactrium spp. (tox gene), Coxiella burnettii; Cryptococcus neoformans, Cryptococcus gattii; Cryptosporidium parvum, Cytomegalovirus (CMV), Dengue (pan), Entamoeba histolytica, Escherichia coli (aaiC gene), Escherichia coli (aatA gene), Enterococcus facium, Enterococcus faecalis, Enterovirus, Escherichia coli (bfpA gene), Escherichia coli (eae gene), Escherichia coli/Shigella, Escherichia coli (heat-labile enterotoxin), Escherichia coli (heat-stable enterotoxin); Bacterial Infections and Mycoses; Birth Trauma; Cancer; Cardiovascular Diseases; Cervical Insufficiency and Pelvic Anomalies; Cesarean Delivery; Chemically-Induced Disorders; Chorioamnionitis and Membrane Complications; Congenital Birth Defects; Congenital, Hereditary, and Neonatal Diseases and Abnormalities; Congenital Infection; Diarrheal Diseases; Digestive System Diseases; Disorders of Environmental Origin; Endocrine System Diseases; Epilepsy; Eye Diseases; Female Urogenital Diseases and Pregnancy Complications; Giardia spp, Group A Streptococcus, Group B Streptococcus, Haemophilus influenzae, Haemophilus influenzae type B, Human coronavirus 1 (229E), Human coronavirus 2 (NL63), Human coronavirus 3 (OC43), Human coronavirus 4 (HKU1), Hepatitis E virus, Human metapneumovirus (HMPV), Herpes simplex virus 1 (HSV1), Herpes simplex virus 2 (HSV2), Human nucleic acid control (Rnase P), Influenza A, Influenza B, Internal Positive Control (IPC), Japanese encephalitis virus, Klebsiella pneumoniae; PAN Lassa Fever Virus, can cross react with other arenavirus; Lassa Fever Virus target 1 and target 2, Leptospira (pan-serovar), Listeria monocytogenes, Measles, MERS coronavirus (N gene), MERS coronavirus (upE gene), Moraxella catarrhalis, Mumps, MS2 phage for extraction control, Mycobacterium tuberculosis, Mycoplasma pneumoniae, Neisseria gonorrhoeae, Neisseria meningitidis, Nipah virus, Norovirus GI, Norovirus GII, Orientia tsutsugamushi, Parechovirus, Parvovirus B19 VP2; Parainfluenza virus type 1, type 2, type 3 and type 4; Plasmodium falciparum, Plasmodium vivax, Pneumocystis jirovecii, Pseudomonas aeruginosa, Respiratory syncytical virus (RSV), Rhinovirus, Rickettsia spp., Rift Valley Fever, Rotavirus A, Rotavirus B, Rotavirus C; Global Health; Heart Diseases; Hemic and Lymphatic Diseases; HIV; Immune System Disease; Injury; Kidney Disease; Liver Disease; Lower Respiratory Infections; Malaria; Malnutrition; Malpresentation Before Labor; Maternal Circulatory and Respiratory Diseases; Maternal Diabetes; Maternal HIV; Maternal Hypertension; Maternal Infection; Maternal Injury and Accident; Maternal Medication or Toxic Exposure; Maternal Nutritional Disorder; Maternal Surgical and Medical Procedures; Measles; Meningitis/Encephalitis; Motor Neuron Disease; Multiple Gestation; Musculoskeletal Diseases; Neonatal Aspiration Syndromes; Neonatal Encephalopathy; Neonatal Preterm Birth Complications; Neonatal Sepsis; Neoplasms; Nervous System Diseases; Nutritional and Metabolic Diseases; Obstructed Labor and Fetal Malpresentation; Other Disorders of Fluid, Electrolyte and Acid-Base Balance; Other Endocrine, Metabolic, Blood and Immune Disorders; Other Gastrointestinal Disease; Other Immunodeficiencies; Other Infections; Other Injury; Other Labor and Delivery Complications; Other Maternal Factor; Other Neonatal Disorders; Other Neurological Disorders; Other Nutritional Deficiencies; Other Respiratory Diseases; Other Skin and Subcutaneous Diseases; Paralytic Ileus and Intestinal Obstruction; Parasitic Diseases; Pathological Conditions, Signs and Symptoms; Perinatal Asphyxia/Hypoxia; Placental Complications; Poisoning; Premature Rupture of Membranes; Preterm Labor or Delivery; Prolapsed Cord; Public Health; Respiratory Tract Diseases; Road Injuries; Sepsis; Sickle Cell Disorders; Skin and Connective Tissue Diseases; Spontaneous Abortion; Stomatognathic Diseases; Sudden Infant Death Syndrome (SIDS); Syphilis; Tuberculosis (TB); Umbilical Cord Complications; Upper Respiratory Infections; Uterine Fluid Disorders; Uterine Rupture; Virus Diseases; Wounds and Injuries |
doi:10.15139/S3/PMAAWG | CHAMPS Limited Dataset, v4.2 | <|begin_of_text|><|start_header_id|>system<|end_header_id|> You are a research archivist expert in dataset metadata. Answer the question truthfully. <|eot_id|><|start_header_id|>user<|end_header_id|> Here is the Description of a dataset. Description:'(rev. 2021-04-01) Request dataset here: https://champshealth.org/data-access/ Version 4.2 of the standard, limited CHAMPS dataset included these files: case demographics (including MITS measurements), verbal autopsy, DeCoDe results, TAC results, and lab results. Sixteen new columns were added to this dataset; one column was renamed. This dataset is updated monthly. The version of this dataset changes quarterly when a revised ICD-10 mapping document is uploaded.</br' . Please return only a json list of at most 3 Keywords corresponding to the Description:.<|eot_id|><|start_header_id|>assistant<|end_header_id|> {"Answer" : ["Anemias","Assays: Bordatella spp., C. difficile, C. diphtheria, H. influenzae, Arenavirus/Lassa Fever, MERS coronavirus, Salmonella spp., V. cholerae, Acinetobacter baumannii, Adenovirus, Adenovirus 40/41, Aeromonas spp., Ascaris lumbricoides, Astrovirus, Bartonella spp.","Bordetella parapertussi, Bordetella bronchiseptica","Bordetella pertussis, Bordetella holmseii","Bordetella pertussis (pertussis toxin), Brucellaspp., Burkholderia pseudomallei, C. difficile paLOC, C. difficile tcdA, C. difficile tcdB, Campylobacter coli, Campylobacter jejuni, Candida albicans, Crimean-Congo Hemorrhagic Fever virus (CCHF), Chikungunya virus, Chlamydia pneumoniae, Chlamydia trachomatis, Corynebacterium diptheriae","Corynebacterium ulcerans, Corynebacterium pseudotuberculosis","Corynebactrium spp. (tox gene), Coxiella burnettii","Cryptococcus neoformans, Cryptococcus gattii","Cryptosporidium parvum, Cytomegalovirus (CMV), Dengue (pan), Entamoeba histolytica, Escherichia coli (aaiC gene), Escherichia coli (aatA gene), Enterococcus facium, Enterococcus faecalis, Enterovirus, Escherichia coli (bfpA gene), Escherichia coli (eae gene), Escherichia coli/Shigella, Escherichia coli (heat-labile enterotoxin), Escherichia coli (heat-stable enterotoxin)","Bacterial Infections and Mycoses","Birth Trauma","Cancer","Cardiovascular Diseases","Cervical Insufficiency and Pelvic Anomalies","Cesarean Delivery","Chemically-Induced Disorders","Chorioamnionitis and Membrane Complications","Congenital Birth Defects","Congenital, Hereditary, and Neonatal Diseases and Abnormalities","Congenital Infection","Diarrheal Diseases","Digestive System Diseases","Disorders of Environmental Origin","Endocrine System Diseases","Epilepsy","Eye Diseases","Female Urogenital Diseases and Pregnancy Complications","Giardia spp, Group A Streptococcus, Group B Streptococcus, Haemophilus influenzae, Haemophilus influenzae type B, Human coronavirus 1 (229E), Human coronavirus 2 (NL63), Human coronavirus 3 (OC43), Human coronavirus 4 (HKU1), Hepatitis E virus, Human metapneumovirus (HMPV), Herpes simplex virus 1 (HSV1), Herpes simplex virus 2 (HSV2), Human nucleic acid control (Rnase P), Influenza A, Influenza B, Internal Positive Control (IPC), Japanese encephalitis virus, Klebsiella pneumoniae","PAN Lassa Fever Virus, can cross react with other arenavirus","Lassa Fever Virus target 1 and target 2, Leptospira (pan-serovar), Listeria monocytogenes, Measles, MERS coronavirus (N gene), MERS coronavirus (upE gene), Moraxella catarrhalis, Mumps, MS2 phage for extraction control, Mycobacterium tuberculosis, Mycoplasma pneumoniae, Neisseria gonorrhoeae, Neisseria meningitidis, Nipah virus, Norovirus GI, Norovirus GII, Orientia tsutsugamushi, Parechovirus, Parvovirus B19 VP2","Parainfluenza virus type 1, type 2, type 3 and type 4","Plasmodium falciparum, Plasmodium vivax, Pneumocystis jirovecii, Pseudomonas aeruginosa, Respiratory syncytical virus (RSV), Rhinovirus, Rickettsia spp., Rift Valley Fever, Rotavirus A, Rotavirus B, Rotavirus C","Global Health","Heart Diseases","Hemic and Lymphatic Diseases","HIV","Immune System Disease","Injury","Kidney Disease","Liver Disease","Lower Respiratory Infections","Malaria","Malnutrition","Malpresentation Before Labor","Maternal Circulatory and Respiratory Diseases","Maternal Diabetes","Maternal HIV","Maternal Hypertension","Maternal Infection","Maternal Injury and Accident","Maternal Medication or Toxic Exposure","Maternal Nutritional Disorder","Maternal Surgical and Medical Procedures","Measles","Meningitis/Encephalitis","Motor Neuron Disease","Multiple Gestation","Musculoskeletal Diseases","Neonatal Aspiration Syndromes","Neonatal Encephalopathy","Neonatal Preterm Birth Complications","Neonatal Sepsis","Neoplasms","Nervous System Diseases","Nutritional and Metabolic Diseases","Obstructed Labor and Fetal Malpresentation","Other Disorders of Fluid, Electrolyte and Acid-Base Balance","Other Endocrine, Metabolic, Blood and Immune Disorders","Other Gastrointestinal Disease","Other Immunodeficiencies","Other Infections","Other Injury","Other Labor and Delivery Complications","Other Maternal Factor","Other Neonatal Disorders","Other Neurological Disorders","Other Nutritional Deficiencies","Other Respiratory Diseases","Other Skin and Subcutaneous Diseases","Paralytic Ileus and Intestinal Obstruction","Parasitic Diseases","Pathological Conditions, Signs and Symptoms","Perinatal Asphyxia/Hypoxia","Placental Complications","Poisoning","Premature Rupture of Membranes","Preterm Labor or Delivery","Prolapsed Cord","Public Health","Respiratory Tract Diseases","Road Injuries","Sepsis","Sickle Cell Disorders","Skin and Connective Tissue Diseases","Spontaneous Abortion","Stomatognathic Diseases","Sudden Infant Death Syndrome (SIDS)","Syphilis","Tuberculosis (TB)","Umbilical Cord Complications","Upper Respiratory Infections","Uterine Fluid Disorders","Uterine Rupture","Virus Diseases","Wounds and Injuries"]} <|eot_id|> | Here is the Description of a dataset. Description:'(rev. 2021-04-01) Request dataset here: https://champshealth.org/data-access/ Version 4.2 of the standard, limited CHAMPS dataset included these files: case demographics (including MITS measurements), verbal autopsy, DeCoDe results, TAC results, and lab results. Sixteen new columns were added to this dataset; one column was renamed. This dataset is updated monthly. The version of this dataset changes quarterly when a revised ICD-10 mapping document is uploaded.</br' . Please return only a json list of at most 3 Keywords corresponding to the Description:. | (rev. 2021-04-01) Request dataset here: https://champshealth.org/data-access/ Version 4.2 of the standard, limited CHAMPS dataset included these files: case demographics (including MITS measurements), verbal autopsy, DeCoDe results, TAC results, and lab results. Sixteen new columns were added to this dataset; one column was renamed. This dataset is updated monthly. The version of this dataset changes quarterly when a revised ICD-10 mapping document is uploaded.</br | Social Sciences | Anemias; Assays: Bordatella spp., C. difficile, C. diphtheria, H. influenzae, Arenavirus/Lassa Fever, MERS coronavirus, Salmonella spp., V. cholerae, Acinetobacter baumannii, Adenovirus, Adenovirus 40/41, Aeromonas spp., Ascaris lumbricoides, Astrovirus, Bartonella spp.; Bordetella parapertussi, Bordetella bronchiseptica; Bordetella pertussis, Bordetella holmseii; Bordetella pertussis (pertussis toxin), Brucellaspp., Burkholderia pseudomallei, C. difficile paLOC, C. difficile tcdA, C. difficile tcdB, Campylobacter coli, Campylobacter jejuni, Candida albicans, Crimean-Congo Hemorrhagic Fever virus (CCHF), Chikungunya virus, Chlamydia pneumoniae, Chlamydia trachomatis, Corynebacterium diptheriae; Corynebacterium ulcerans, Corynebacterium pseudotuberculosis; Corynebactrium spp. (tox gene), Coxiella burnettii; Cryptococcus neoformans, Cryptococcus gattii; Cryptosporidium parvum, Cytomegalovirus (CMV), Dengue (pan), Entamoeba histolytica, Escherichia coli (aaiC gene), Escherichia coli (aatA gene), Enterococcus facium, Enterococcus faecalis, Enterovirus, Escherichia coli (bfpA gene), Escherichia coli (eae gene), Escherichia coli/Shigella, Escherichia coli (heat-labile enterotoxin), Escherichia coli (heat-stable enterotoxin); Bacterial Infections and Mycoses; Birth Trauma; Cancer; Cardiovascular Diseases; Cervical Insufficiency and Pelvic Anomalies; Cesarean Delivery; Chemically-Induced Disorders; Chorioamnionitis and Membrane Complications; Congenital Birth Defects; Congenital, Hereditary, and Neonatal Diseases and Abnormalities; Congenital Infection; Diarrheal Diseases; Digestive System Diseases; Disorders of Environmental Origin; Endocrine System Diseases; Epilepsy; Eye Diseases; Female Urogenital Diseases and Pregnancy Complications; Giardia spp, Group A Streptococcus, Group B Streptococcus, Haemophilus influenzae, Haemophilus influenzae type B, Human coronavirus 1 (229E), Human coronavirus 2 (NL63), Human coronavirus 3 (OC43), Human coronavirus 4 (HKU1), Hepatitis E virus, Human metapneumovirus (HMPV), Herpes simplex virus 1 (HSV1), Herpes simplex virus 2 (HSV2), Human nucleic acid control (Rnase P), Influenza A, Influenza B, Internal Positive Control (IPC), Japanese encephalitis virus, Klebsiella pneumoniae; PAN Lassa Fever Virus, can cross react with other arenavirus; Lassa Fever Virus target 1 and target 2, Leptospira (pan-serovar), Listeria monocytogenes, Measles, MERS coronavirus (N gene), MERS coronavirus (upE gene), Moraxella catarrhalis, Mumps, MS2 phage for extraction control, Mycobacterium tuberculosis, Mycoplasma pneumoniae, Neisseria gonorrhoeae, Neisseria meningitidis, Nipah virus, Norovirus GI, Norovirus GII, Orientia tsutsugamushi, Parechovirus, Parvovirus B19 VP2; Parainfluenza virus type 1, type 2, type 3 and type 4; Plasmodium falciparum, Plasmodium vivax, Pneumocystis jirovecii, Pseudomonas aeruginosa, Respiratory syncytical virus (RSV), Rhinovirus, Rickettsia spp., Rift Valley Fever, Rotavirus A, Rotavirus B, Rotavirus C; Global Health; Heart Diseases; Hemic and Lymphatic Diseases; HIV; Immune System Disease; Injury; Kidney Disease; Liver Disease; Lower Respiratory Infections; Malaria; Malnutrition; Malpresentation Before Labor; Maternal Circulatory and Respiratory Diseases; Maternal Diabetes; Maternal HIV; Maternal Hypertension; Maternal Infection; Maternal Injury and Accident; Maternal Medication or Toxic Exposure; Maternal Nutritional Disorder; Maternal Surgical and Medical Procedures; Measles; Meningitis/Encephalitis; Motor Neuron Disease; Multiple Gestation; Musculoskeletal Diseases; Neonatal Aspiration Syndromes; Neonatal Encephalopathy; Neonatal Preterm Birth Complications; Neonatal Sepsis; Neoplasms; Nervous System Diseases; Nutritional and Metabolic Diseases; Obstructed Labor and Fetal Malpresentation; Other Disorders of Fluid, Electrolyte and Acid-Base Balance; Other Endocrine, Metabolic, Blood and Immune Disorders; Other Gastrointestinal Disease; Other Immunodeficiencies; Other Infections; Other Injury; Other Labor and Delivery Complications; Other Maternal Factor; Other Neonatal Disorders; Other Neurological Disorders; Other Nutritional Deficiencies; Other Respiratory Diseases; Other Skin and Subcutaneous Diseases; Paralytic Ileus and Intestinal Obstruction; Parasitic Diseases; Pathological Conditions, Signs and Symptoms; Perinatal Asphyxia/Hypoxia; Placental Complications; Poisoning; Premature Rupture of Membranes; Preterm Labor or Delivery; Prolapsed Cord; Public Health; Respiratory Tract Diseases; Road Injuries; Sepsis; Sickle Cell Disorders; Skin and Connective Tissue Diseases; Spontaneous Abortion; Stomatognathic Diseases; Sudden Infant Death Syndrome (SIDS); Syphilis; Tuberculosis (TB); Umbilical Cord Complications; Upper Respiratory Infections; Uterine Fluid Disorders; Uterine Rupture; Virus Diseases; Wounds and Injuries |
doi:10.15139/S3/QXRH9S | NGO Health Service Delivery Project (NHSDP) Baseline Rural/Urban Survey 2014 | <|begin_of_text|><|start_header_id|>system<|end_header_id|> You are a research archivist expert in dataset metadata. Answer the question truthfully. <|eot_id|><|start_header_id|>user<|end_header_id|> Here is the Description of a dataset. Description:'The United States Agency for International Development (USAID)/Bangladesh requested an external impact evaluation of the “Nongovernmental Organization (NGO) Health Service Delivery Project” (NHSDP) program that was awarded to Pathfinder International in December 2012. The impact evaluation used a difference-in-difference (DID) strategy to determine program impact. This design requires collecting baseline and endline data in program intervention areas and similar comparison areas, which serve as the counterfactual for the impact evaluation. The 2014 NHSDP baseline survey is the first of the two surveys. The main objective of the survey was to measure USAID performance indicators related to health and family planning that the program seeks to improve in program intervention areas and in similar comparison areas (where NHSDP is not in oper' . Please return only a json list of at most 3 Keywords corresponding to the Description:.<|eot_id|><|start_header_id|>assistant<|end_header_id|> {"Answer" : ["Bangladesh","Child health","Family planning","Maternal health"]} <|eot_id|> | Here is the Description of a dataset. Description:'The United States Agency for International Development (USAID)/Bangladesh requested an external impact evaluation of the “Nongovernmental Organization (NGO) Health Service Delivery Project” (NHSDP) program that was awarded to Pathfinder International in December 2012. The impact evaluation used a difference-in-difference (DID) strategy to determine program impact. This design requires collecting baseline and endline data in program intervention areas and similar comparison areas, which serve as the counterfactual for the impact evaluation. The 2014 NHSDP baseline survey is the first of the two surveys. The main objective of the survey was to measure USAID performance indicators related to health and family planning that the program seeks to improve in program intervention areas and in similar comparison areas (where NHSDP is not in oper' . Please return only a json list of at most 3 Keywords corresponding to the Description:. | The United States Agency for International Development (USAID)/Bangladesh requested an external impact evaluation of the “Nongovernmental Organization (NGO) Health Service Delivery Project” (NHSDP) program that was awarded to Pathfinder International in December 2012. The impact evaluation used a difference-in-difference (DID) strategy to determine program impact. This design requires collecting baseline and endline data in program intervention areas and similar comparison areas, which serve as the counterfactual for the impact evaluation. The 2014 NHSDP baseline survey is the first of the two surveys. The main objective of the survey was to measure USAID performance indicators related to health and family planning that the program seeks to improve in program intervention areas and in similar comparison areas (where NHSDP is not in oper | Medicine, Health and Life Sciences | Bangladesh; Child health; Family planning; Maternal health |
doi:10.15139/S3/QXRH9S | NGO Health Service Delivery Project (NHSDP) Baseline Rural/Urban Survey 2014 | <|begin_of_text|><|start_header_id|>system<|end_header_id|> You are a research archivist expert in dataset metadata. Answer the question truthfully. <|eot_id|><|start_header_id|>user<|end_header_id|> Here is the Description of a dataset. Description:'The United States Agency for International Development (USAID)/Bangladesh requested an external impact evaluation of the “Nongovernmental Organization (NGO) Health Service Delivery Project” (NHSDP) program that was awarded to Pathfinder International in December 2012. The impact evaluation used a difference-in-difference (DID) strategy to determine program impact. This design requires collecting baseline and endline data in program intervention areas and similar comparison areas, which serve as the counterfactual for the impact evaluation. The 2014 NHSDP baseline survey is the first of the two surveys. The main objective of the survey was to measure USAID performance indicators related to health and family planning that the program seeks to improve in program intervention areas and in similar comparison areas (where NHSDP is not in oper' . Please return only a json list of at most 3 Keywords corresponding to the Description:.<|eot_id|><|start_header_id|>assistant<|end_header_id|> {"Answer" : ["Bangladesh","Child health","Family planning","Maternal health"]} <|eot_id|> | Here is the Description of a dataset. Description:'The United States Agency for International Development (USAID)/Bangladesh requested an external impact evaluation of the “Nongovernmental Organization (NGO) Health Service Delivery Project” (NHSDP) program that was awarded to Pathfinder International in December 2012. The impact evaluation used a difference-in-difference (DID) strategy to determine program impact. This design requires collecting baseline and endline data in program intervention areas and similar comparison areas, which serve as the counterfactual for the impact evaluation. The 2014 NHSDP baseline survey is the first of the two surveys. The main objective of the survey was to measure USAID performance indicators related to health and family planning that the program seeks to improve in program intervention areas and in similar comparison areas (where NHSDP is not in oper' . Please return only a json list of at most 3 Keywords corresponding to the Description:. | The United States Agency for International Development (USAID)/Bangladesh requested an external impact evaluation of the “Nongovernmental Organization (NGO) Health Service Delivery Project” (NHSDP) program that was awarded to Pathfinder International in December 2012. The impact evaluation used a difference-in-difference (DID) strategy to determine program impact. This design requires collecting baseline and endline data in program intervention areas and similar comparison areas, which serve as the counterfactual for the impact evaluation. The 2014 NHSDP baseline survey is the first of the two surveys. The main objective of the survey was to measure USAID performance indicators related to health and family planning that the program seeks to improve in program intervention areas and in similar comparison areas (where NHSDP is not in oper | Social Sciences | Bangladesh; Child health; Family planning; Maternal health |
doi:10.15139/S3/S2DULX | Data for RICHS Seasonally variant gene expression in full‐term human placenta | <|begin_of_text|><|start_header_id|>system<|end_header_id|> You are a research archivist expert in dataset metadata. Answer the question truthfully. <|eot_id|><|start_header_id|>user<|end_header_id|> Here is the Description of a dataset. Description:'Seasonal exposures influence human health and development. The placenta, as a mediator of the maternal and fetal systems and a regulator of development, is an ideal tissue to understand the biological pathways underlying relationships between season of birth and later life health outcomes. Here, we conducted a differential expression (DE) analysis of season of birth in full‐term human placental tissue to evaluate whether the placenta may be influenced by seasonal cues. Of the analyzed transcripts, 583 displayed DE between summer and winter births (False Discovery Rate [FDR] q < .05); among these, BHLHE40, MIR210HG, and HILPDA had increased expression among winter births (Bonferroni P < .05). Enrichment analyses of the seasonally variant genes between summer and winter births indicated overrepresentation of transcription factors HIF1A, V' . Please return only a json list of at most 3 Keywords corresponding to the Description:.<|eot_id|><|start_header_id|>assistant<|end_header_id|> {"Answer" : ["placenta","RNA"]} <|eot_id|> | Here is the Description of a dataset. Description:'Seasonal exposures influence human health and development. The placenta, as a mediator of the maternal and fetal systems and a regulator of development, is an ideal tissue to understand the biological pathways underlying relationships between season of birth and later life health outcomes. Here, we conducted a differential expression (DE) analysis of season of birth in full‐term human placental tissue to evaluate whether the placenta may be influenced by seasonal cues. Of the analyzed transcripts, 583 displayed DE between summer and winter births (False Discovery Rate [FDR] q < .05); among these, BHLHE40, MIR210HG, and HILPDA had increased expression among winter births (Bonferroni P < .05). Enrichment analyses of the seasonally variant genes between summer and winter births indicated overrepresentation of transcription factors HIF1A, V' . Please return only a json list of at most 3 Keywords corresponding to the Description:. | Seasonal exposures influence human health and development. The placenta, as a mediator of the maternal and fetal systems and a regulator of development, is an ideal tissue to understand the biological pathways underlying relationships between season of birth and later life health outcomes. Here, we conducted a differential expression (DE) analysis of season of birth in full‐term human placental tissue to evaluate whether the placenta may be influenced by seasonal cues. Of the analyzed transcripts, 583 displayed DE between summer and winter births (False Discovery Rate [FDR] q < .05); among these, BHLHE40, MIR210HG, and HILPDA had increased expression among winter births (Bonferroni P < .05). Enrichment analyses of the seasonally variant genes between summer and winter births indicated overrepresentation of transcription factors HIF1A, V | Medicine, Health and Life Sciences | placenta; RNA |
doi:10.15139/S3/SIIYCO | Caregivers Recall of Antimalarial Treatment for their Children at Health Clinics in Southern Mali | <|begin_of_text|><|start_header_id|>system<|end_header_id|> You are a research archivist expert in dataset metadata. Answer the question truthfully. <|eot_id|><|start_header_id|>user<|end_header_id|> Here is the Description of a dataset. Description:'This research aims to assess the validity of the primary coverage indicator for malaria treatment collected by household surveys (e.g. DHS) from interviews with mothers/caregivers of children taken for treatment of fevers at health facilities. The study used a prospective case-control design. The study identified mothers/caregivers of children with suspected malaria fevers at selected health facilities. Caregivers were asked if they could be followed-up at their home within 2 weeks, where they were asked questions related to their recall of the treatment, if any, their child received during the clinic visit. Data collection was be split between the period immediately prior to SMC (June) and during the period of monthly SMC implementation (July-November)' . Please return only a json list of at most 3 Keywords corresponding to the Description:.<|eot_id|><|start_header_id|>assistant<|end_header_id|> {"Answer" : ["ACTs","Caregiver","Health facilities","Malaria","Mali","Mother","Recall","Validity testing"]} <|eot_id|> | Here is the Description of a dataset. Description:'This research aims to assess the validity of the primary coverage indicator for malaria treatment collected by household surveys (e.g. DHS) from interviews with mothers/caregivers of children taken for treatment of fevers at health facilities. The study used a prospective case-control design. The study identified mothers/caregivers of children with suspected malaria fevers at selected health facilities. Caregivers were asked if they could be followed-up at their home within 2 weeks, where they were asked questions related to their recall of the treatment, if any, their child received during the clinic visit. Data collection was be split between the period immediately prior to SMC (June) and during the period of monthly SMC implementation (July-November)' . Please return only a json list of at most 3 Keywords corresponding to the Description:. | This research aims to assess the validity of the primary coverage indicator for malaria treatment collected by household surveys (e.g. DHS) from interviews with mothers/caregivers of children taken for treatment of fevers at health facilities. The study used a prospective case-control design. The study identified mothers/caregivers of children with suspected malaria fevers at selected health facilities. Caregivers were asked if they could be followed-up at their home within 2 weeks, where they were asked questions related to their recall of the treatment, if any, their child received during the clinic visit. Data collection was be split between the period immediately prior to SMC (June) and during the period of monthly SMC implementation (July-November) | Medicine, Health and Life Sciences | ACTs; Caregiver; Health facilities; Malaria; Mali; Mother; Recall; Validity testing |
doi:10.15139/S3/STQXUU | Formative Assessment for the Development of an Undergraduate Research Experience for College Students from Farmworker Families | <|begin_of_text|><|start_header_id|>system<|end_header_id|> You are a research archivist expert in dataset metadata. Answer the question truthfully. <|eot_id|><|start_header_id|>user<|end_header_id|> Here is the Description of a dataset. Description:'College students from migrant and seasonal farmworker (MSFW) families face many barriers to educational attainment in the United States: sporadic schooling experiences, cultural and communication barriers, low pay, discrimination, and health issues from farm work. Retaining students from MSFW families in higher education and research is critical for addressing educational and health inequities. In an effort to develop experiences that could serve as a pipeline for MSFW undergraduate students into research careers, we conducted interviews to inform program development by exploring the research experiences of university students and recent graduates from MSFW families' . Please return only a json list of at most 3 Keywords corresponding to the Description:.<|eot_id|><|start_header_id|>assistant<|end_header_id|> {"Answer" : ["agricultural workers","farmworkers","science education"]} <|eot_id|> | Here is the Description of a dataset. Description:'College students from migrant and seasonal farmworker (MSFW) families face many barriers to educational attainment in the United States: sporadic schooling experiences, cultural and communication barriers, low pay, discrimination, and health issues from farm work. Retaining students from MSFW families in higher education and research is critical for addressing educational and health inequities. In an effort to develop experiences that could serve as a pipeline for MSFW undergraduate students into research careers, we conducted interviews to inform program development by exploring the research experiences of university students and recent graduates from MSFW families' . Please return only a json list of at most 3 Keywords corresponding to the Description:. | College students from migrant and seasonal farmworker (MSFW) families face many barriers to educational attainment in the United States: sporadic schooling experiences, cultural and communication barriers, low pay, discrimination, and health issues from farm work. Retaining students from MSFW families in higher education and research is critical for addressing educational and health inequities. In an effort to develop experiences that could serve as a pipeline for MSFW undergraduate students into research careers, we conducted interviews to inform program development by exploring the research experiences of university students and recent graduates from MSFW families | Medicine, Health and Life Sciences | agricultural workers; farmworkers; science education |
doi:10.15139/S3/STQXUU | Formative Assessment for the Development of an Undergraduate Research Experience for College Students from Farmworker Families | <|begin_of_text|><|start_header_id|>system<|end_header_id|> You are a research archivist expert in dataset metadata. Answer the question truthfully. <|eot_id|><|start_header_id|>user<|end_header_id|> Here is the Description of a dataset. Description:'College students from migrant and seasonal farmworker (MSFW) families face many barriers to educational attainment in the United States: sporadic schooling experiences, cultural and communication barriers, low pay, discrimination, and health issues from farm work. Retaining students from MSFW families in higher education and research is critical for addressing educational and health inequities. In an effort to develop experiences that could serve as a pipeline for MSFW undergraduate students into research careers, we conducted interviews to inform program development by exploring the research experiences of university students and recent graduates from MSFW families' . Please return only a json list of at most 3 Keywords corresponding to the Description:.<|eot_id|><|start_header_id|>assistant<|end_header_id|> {"Answer" : ["agricultural workers","farmworkers","science education"]} <|eot_id|> | Here is the Description of a dataset. Description:'College students from migrant and seasonal farmworker (MSFW) families face many barriers to educational attainment in the United States: sporadic schooling experiences, cultural and communication barriers, low pay, discrimination, and health issues from farm work. Retaining students from MSFW families in higher education and research is critical for addressing educational and health inequities. In an effort to develop experiences that could serve as a pipeline for MSFW undergraduate students into research careers, we conducted interviews to inform program development by exploring the research experiences of university students and recent graduates from MSFW families' . Please return only a json list of at most 3 Keywords corresponding to the Description:. | College students from migrant and seasonal farmworker (MSFW) families face many barriers to educational attainment in the United States: sporadic schooling experiences, cultural and communication barriers, low pay, discrimination, and health issues from farm work. Retaining students from MSFW families in higher education and research is critical for addressing educational and health inequities. In an effort to develop experiences that could serve as a pipeline for MSFW undergraduate students into research careers, we conducted interviews to inform program development by exploring the research experiences of university students and recent graduates from MSFW families | Social Sciences | agricultural workers; farmworkers; science education |
doi:10.15139/S3/SWNWJG | Utilization of No Tobacco Sale Orders against Retailers that Repeatedly Sell to Minors, 2015-2019 | <|begin_of_text|><|start_header_id|>system<|end_header_id|> You are a research archivist expert in dataset metadata. Answer the question truthfully. <|eot_id|><|start_header_id|>user<|end_header_id|> Here is the Description of a dataset. Description:'This dataset contains documentation from an assessment of Food and Drug Administration compliance check and enforcement data. We sought to assess the FDA's utilization of no tobacco sale orders (NTSOs)' . Please return only a json list of at most 3 Keywords corresponding to the Description:.<|eot_id|><|start_header_id|>assistant<|end_header_id|> {"Answer" : ["Compliance","Enforcement","Tobacco","Youth Access"]} <|eot_id|> | Here is the Description of a dataset. Description:'This dataset contains documentation from an assessment of Food and Drug Administration compliance check and enforcement data. We sought to assess the FDA's utilization of no tobacco sale orders (NTSOs)' . Please return only a json list of at most 3 Keywords corresponding to the Description:. | This dataset contains documentation from an assessment of Food and Drug Administration compliance check and enforcement data. We sought to assess the FDA's utilization of no tobacco sale orders (NTSOs) | Medicine, Health and Life Sciences | Compliance; Enforcement; Tobacco; Youth Access |
doi:10.15139/S3/SWNWJG | Utilization of No Tobacco Sale Orders against Retailers that Repeatedly Sell to Minors, 2015-2019 | <|begin_of_text|><|start_header_id|>system<|end_header_id|> You are a research archivist expert in dataset metadata. Answer the question truthfully. <|eot_id|><|start_header_id|>user<|end_header_id|> Here is the Description of a dataset. Description:'This dataset contains documentation from an assessment of Food and Drug Administration compliance check and enforcement data. We sought to assess the FDA's utilization of no tobacco sale orders (NTSOs)' . Please return only a json list of at most 3 Keywords corresponding to the Description:.<|eot_id|><|start_header_id|>assistant<|end_header_id|> {"Answer" : ["Compliance","Enforcement","Tobacco","Youth Access"]} <|eot_id|> | Here is the Description of a dataset. Description:'This dataset contains documentation from an assessment of Food and Drug Administration compliance check and enforcement data. We sought to assess the FDA's utilization of no tobacco sale orders (NTSOs)' . Please return only a json list of at most 3 Keywords corresponding to the Description:. | This dataset contains documentation from an assessment of Food and Drug Administration compliance check and enforcement data. We sought to assess the FDA's utilization of no tobacco sale orders (NTSOs) | Social Sciences | Compliance; Enforcement; Tobacco; Youth Access |
doi:10.15139/S3/T5NYHD | Blackbeard Mission 6 | <|begin_of_text|><|start_header_id|>system<|end_header_id|> You are a research archivist expert in dataset metadata. Answer the question truthfully. <|eot_id|><|start_header_id|>user<|end_header_id|> Here is the Description of a dataset. Description:'Data collected by the acoustic wave glider Blackbeard on Mission 6 in Onslow Bay 2017-08-01 to 2017-08-09' . Please return only a json list of at most 3 Keywords corresponding to the Description:.<|eot_id|><|start_header_id|>assistant<|end_header_id|> {"Answer" : ["fish sound","marine soundscapes","passive acoustic monitoring"]} <|eot_id|> | Here is the Description of a dataset. Description:'Data collected by the acoustic wave glider Blackbeard on Mission 6 in Onslow Bay 2017-08-01 to 2017-08-09' . Please return only a json list of at most 3 Keywords corresponding to the Description:. | Data collected by the acoustic wave glider Blackbeard on Mission 6 in Onslow Bay 2017-08-01 to 2017-08-09 | Medicine, Health and Life Sciences | fish sound; marine soundscapes; passive acoustic monitoring |
doi:10.15139/S3/T5NYHD | Blackbeard Mission 6 | <|begin_of_text|><|start_header_id|>system<|end_header_id|> You are a research archivist expert in dataset metadata. Answer the question truthfully. <|eot_id|><|start_header_id|>user<|end_header_id|> Here is the Description of a dataset. Description:'Data collected by the acoustic wave glider Blackbeard on Mission 6 in Onslow Bay 2017-08-01 to 2017-08-09' . Please return only a json list of at most 3 Keywords corresponding to the Description:.<|eot_id|><|start_header_id|>assistant<|end_header_id|> {"Answer" : ["fish sound","marine soundscapes","passive acoustic monitoring"]} <|eot_id|> | Here is the Description of a dataset. Description:'Data collected by the acoustic wave glider Blackbeard on Mission 6 in Onslow Bay 2017-08-01 to 2017-08-09' . Please return only a json list of at most 3 Keywords corresponding to the Description:. | Data collected by the acoustic wave glider Blackbeard on Mission 6 in Onslow Bay 2017-08-01 to 2017-08-09 | Physics | fish sound; marine soundscapes; passive acoustic monitoring |
doi:10.15139/S3/UBWSVZ | Replication Data for: Xu/Yan et al., 'Positive supercoiling favors transcription', NAR 2022 | <|begin_of_text|><|start_header_id|>system<|end_header_id|> You are a research archivist expert in dataset metadata. Answer the question truthfully. <|eot_id|><|start_header_id|>user<|end_header_id|> Here is the Description of a dataset. Description:'Excel and Matlab format data files as well as simple M-files to plot the Matlab formatted data are included' . Please return only a json list of at most 3 Keywords corresponding to the Description:.<|eot_id|><|start_header_id|>assistant<|end_header_id|> {"Answer" : ["lac repressor","magnetic tweezers","RNA polymerase","supercoiling","tethered particle motion"]} <|eot_id|> | Here is the Description of a dataset. Description:'Excel and Matlab format data files as well as simple M-files to plot the Matlab formatted data are included' . Please return only a json list of at most 3 Keywords corresponding to the Description:. | Excel and Matlab format data files as well as simple M-files to plot the Matlab formatted data are included | Medicine, Health and Life Sciences | lac repressor; magnetic tweezers; RNA polymerase; supercoiling; tethered particle motion |
doi:10.15139/S3/UBWSVZ | Replication Data for: Xu/Yan et al., 'Positive supercoiling favors transcription', NAR 2022 | <|begin_of_text|><|start_header_id|>system<|end_header_id|> You are a research archivist expert in dataset metadata. Answer the question truthfully. <|eot_id|><|start_header_id|>user<|end_header_id|> Here is the Description of a dataset. Description:'Excel and Matlab format data files as well as simple M-files to plot the Matlab formatted data are included' . Please return only a json list of at most 3 Keywords corresponding to the Description:.<|eot_id|><|start_header_id|>assistant<|end_header_id|> {"Answer" : ["lac repressor","magnetic tweezers","RNA polymerase","supercoiling","tethered particle motion"]} <|eot_id|> | Here is the Description of a dataset. Description:'Excel and Matlab format data files as well as simple M-files to plot the Matlab formatted data are included' . Please return only a json list of at most 3 Keywords corresponding to the Description:. | Excel and Matlab format data files as well as simple M-files to plot the Matlab formatted data are included | Physics | lac repressor; magnetic tweezers; RNA polymerase; supercoiling; tethered particle motion |
doi:10.15139/S3/UZIR0P | Tanzania Lake Zone health facility data 2016 | <|begin_of_text|><|start_header_id|>system<|end_header_id|> You are a research archivist expert in dataset metadata. Answer the question truthfully. <|eot_id|><|start_header_id|>user<|end_header_id|> Here is the Description of a dataset. Description:'MEASURE Evaluation was contracted to conduct a performance evaluation of the Tibu Homa Project, which was implemented in the Lake Zone of Tanzania between March 2011–September 2015. The evaluation used a retrospective, mixed-methods approach. Data sources included a cross-sectional quantitative health facility survey, with both a facility checklist and observational data of health facility visits for children under five years old. Primary outcomes of the evaluation were indicators of quality of care, which are defined by the WHO Health Facility Survey (HFS) and include the Index of Integrated Assessment; correct classification; and correct treatment of cases observed or reviewed in patient records' . Please return only a json list of at most 3 Keywords corresponding to the Description:.<|eot_id|><|start_header_id|>assistant<|end_header_id|> {"Answer" : ["Health facility survey","Integrated management of childhood illness","Malaria","Quality of care","Tanzania"]} <|eot_id|> | Here is the Description of a dataset. Description:'MEASURE Evaluation was contracted to conduct a performance evaluation of the Tibu Homa Project, which was implemented in the Lake Zone of Tanzania between March 2011–September 2015. The evaluation used a retrospective, mixed-methods approach. Data sources included a cross-sectional quantitative health facility survey, with both a facility checklist and observational data of health facility visits for children under five years old. Primary outcomes of the evaluation were indicators of quality of care, which are defined by the WHO Health Facility Survey (HFS) and include the Index of Integrated Assessment; correct classification; and correct treatment of cases observed or reviewed in patient records' . Please return only a json list of at most 3 Keywords corresponding to the Description:. | MEASURE Evaluation was contracted to conduct a performance evaluation of the Tibu Homa Project, which was implemented in the Lake Zone of Tanzania between March 2011–September 2015. The evaluation used a retrospective, mixed-methods approach. Data sources included a cross-sectional quantitative health facility survey, with both a facility checklist and observational data of health facility visits for children under five years old. Primary outcomes of the evaluation were indicators of quality of care, which are defined by the WHO Health Facility Survey (HFS) and include the Index of Integrated Assessment; correct classification; and correct treatment of cases observed or reviewed in patient records | Medicine, Health and Life Sciences | Health facility survey; Integrated management of childhood illness; Malaria; Quality of care; Tanzania |
doi:10.15139/S3/VEMBFM | Alternative Approaches to MDA Coverage Surveys in Uganda | <|begin_of_text|><|start_header_id|>system<|end_header_id|> You are a research archivist expert in dataset metadata. Answer the question truthfully. <|eot_id|><|start_header_id|>user<|end_header_id|> Here is the Description of a dataset. Description:'Coverage surveys are an important tool for programs to evaluate their reporting systems and to determine whether effective MDA coverage has been achieved. However, for various reasons coverage surveys are seldom implemented. Some key challenges are: perceived technical difficulty, lack of resources, and lack of standardized guidance on how to conduct coverage surveys. This protocol seeks to address the 1st and 3rd points by comparing the feasibility of three different coverage survey methods (EPI approach, LQAS, and segmentation). This study was completed all 3 methods in the same district in Uganda. All 3 coverage surveys were integrated surveys, meaning that the questionnaire addressed coverage for ALB, IVM, PZQ, and ZITH. All methods found that the survey coverage was far below the WHO target thresholds. Furthermore, for all drug' . Please return only a json list of at most 3 Keywords corresponding to the Description:.<|eot_id|><|start_header_id|>assistant<|end_header_id|> {"Answer" : ["Lymphatic Filariasis"]} <|eot_id|> | Here is the Description of a dataset. Description:'Coverage surveys are an important tool for programs to evaluate their reporting systems and to determine whether effective MDA coverage has been achieved. However, for various reasons coverage surveys are seldom implemented. Some key challenges are: perceived technical difficulty, lack of resources, and lack of standardized guidance on how to conduct coverage surveys. This protocol seeks to address the 1st and 3rd points by comparing the feasibility of three different coverage survey methods (EPI approach, LQAS, and segmentation). This study was completed all 3 methods in the same district in Uganda. All 3 coverage surveys were integrated surveys, meaning that the questionnaire addressed coverage for ALB, IVM, PZQ, and ZITH. All methods found that the survey coverage was far below the WHO target thresholds. Furthermore, for all drug' . Please return only a json list of at most 3 Keywords corresponding to the Description:. | Coverage surveys are an important tool for programs to evaluate their reporting systems and to determine whether effective MDA coverage has been achieved. However, for various reasons coverage surveys are seldom implemented. Some key challenges are: perceived technical difficulty, lack of resources, and lack of standardized guidance on how to conduct coverage surveys. This protocol seeks to address the 1st and 3rd points by comparing the feasibility of three different coverage survey methods (EPI approach, LQAS, and segmentation). This study was completed all 3 methods in the same district in Uganda. All 3 coverage surveys were integrated surveys, meaning that the questionnaire addressed coverage for ALB, IVM, PZQ, and ZITH. All methods found that the survey coverage was far below the WHO target thresholds. Furthermore, for all drug | Medicine, Health and Life Sciences | Lymphatic Filariasis |
doi:10.15139/S3/VIOTDL | Community Survey of Lymphatic Filariasis Mass Drug Administration Acceptability in Guyana, August 2019 | <|begin_of_text|><|start_header_id|>system<|end_header_id|> You are a research archivist expert in dataset metadata. Answer the question truthfully. <|eot_id|><|start_header_id|>user<|end_header_id|> Here is the Description of a dataset. Description:'A cross-sectional community survey of public perceptions and attitudes relating to Lymphatic Filariasis (LF) and Mass Drug Administration (MDA) elimination efforts was conducted in four regions of Guyana during August 2019 as a component of ongoing LF remapping efforts. Enumerators collected data on respondents' self-rated knowledge of and perception of LF and MDA, as well as historic coverage and compliance with MDA and a validated metric of LF MDA acceptability. General demographic information was also collected' . Please return only a json list of at most 3 Keywords corresponding to the Description:.<|eot_id|><|start_header_id|>assistant<|end_header_id|> {"Answer" : ["Acceptability","Lymphatic Filariasis","Mass Drug Administration"]} <|eot_id|> | Here is the Description of a dataset. Description:'A cross-sectional community survey of public perceptions and attitudes relating to Lymphatic Filariasis (LF) and Mass Drug Administration (MDA) elimination efforts was conducted in four regions of Guyana during August 2019 as a component of ongoing LF remapping efforts. Enumerators collected data on respondents' self-rated knowledge of and perception of LF and MDA, as well as historic coverage and compliance with MDA and a validated metric of LF MDA acceptability. General demographic information was also collected' . Please return only a json list of at most 3 Keywords corresponding to the Description:. | A cross-sectional community survey of public perceptions and attitudes relating to Lymphatic Filariasis (LF) and Mass Drug Administration (MDA) elimination efforts was conducted in four regions of Guyana during August 2019 as a component of ongoing LF remapping efforts. Enumerators collected data on respondents' self-rated knowledge of and perception of LF and MDA, as well as historic coverage and compliance with MDA and a validated metric of LF MDA acceptability. General demographic information was also collected | Medicine, Health and Life Sciences | Acceptability; Lymphatic Filariasis; Mass Drug Administration |
doi:10.15139/S3/WCLFWZ | Dataset for Predictive Modeling of Biological Responses in the Rat Liver using In Vitro Tox21 Bioactivity: Benefits from High-Throughput Toxicokinetics | <|begin_of_text|><|start_header_id|>system<|end_header_id|> You are a research archivist expert in dataset metadata. Answer the question truthfully. <|eot_id|><|start_header_id|>user<|end_header_id|> Here is the Description of a dataset. Description:'Supporting information, data, and script for the manuscript 'Predictive Modeling of Biological Responses in the Rat Liver using In Vitro Tox21 Bioactivity: Benefits from High-Throughput Toxicokinetics' . Please return only a json list of at most 3 Keywords corresponding to the Description:.<|eot_id|><|start_header_id|>assistant<|end_header_id|> {"Answer" : ["Computational Biology","High-Throughput Screening Assays"]} <|eot_id|> | Here is the Description of a dataset. Description:'Supporting information, data, and script for the manuscript 'Predictive Modeling of Biological Responses in the Rat Liver using In Vitro Tox21 Bioactivity: Benefits from High-Throughput Toxicokinetics' . Please return only a json list of at most 3 Keywords corresponding to the Description:. | Supporting information, data, and script for the manuscript 'Predictive Modeling of Biological Responses in the Rat Liver using In Vitro Tox21 Bioactivity: Benefits from High-Throughput Toxicokinetics | Medicine, Health and Life Sciences | Computational Biology; High-Throughput Screening Assays |
doi:10.15139/S3/WOYRUW | Lymphatic Filariasis Positive-Case Follow-up After TAS 2 in Haiti | <|begin_of_text|><|start_header_id|>system<|end_header_id|> You are a research archivist expert in dataset metadata. Answer the question truthfully. <|eot_id|><|start_header_id|>user<|end_header_id|> Here is the Description of a dataset. Description:'Because the cut-off for passing a transmission assessment survey (TAS) is a critical cut-off based on the upper 95% confidence interval of less than 1 or 2% (dependent on primary vector) prevalence of antigenemia among children ages 6 and 7, many implementation units pass TAS with one or more positive FTS results. However, the presence of any FTS positive children in a TAS 2 or TAS 3 indicates possible ongoing transmission. The WHO LF program manager’s manual encourages program managers to conduct follow-up surveys in communities where antigen positive children are found. However, there is currently no published guidance on how this follow-up should be conducted. The goals of this project were to determine the implications of one or more positive FTS results and to provide evidence towards recommendations on how to follow up on these re' . Please return only a json list of at most 3 Keywords corresponding to the Description:.<|eot_id|><|start_header_id|>assistant<|end_header_id|> {"Answer" : ["FTS","Lymphatic Filariasis"]} <|eot_id|> | Here is the Description of a dataset. Description:'Because the cut-off for passing a transmission assessment survey (TAS) is a critical cut-off based on the upper 95% confidence interval of less than 1 or 2% (dependent on primary vector) prevalence of antigenemia among children ages 6 and 7, many implementation units pass TAS with one or more positive FTS results. However, the presence of any FTS positive children in a TAS 2 or TAS 3 indicates possible ongoing transmission. The WHO LF program manager’s manual encourages program managers to conduct follow-up surveys in communities where antigen positive children are found. However, there is currently no published guidance on how this follow-up should be conducted. The goals of this project were to determine the implications of one or more positive FTS results and to provide evidence towards recommendations on how to follow up on these re' . Please return only a json list of at most 3 Keywords corresponding to the Description:. | Because the cut-off for passing a transmission assessment survey (TAS) is a critical cut-off based on the upper 95% confidence interval of less than 1 or 2% (dependent on primary vector) prevalence of antigenemia among children ages 6 and 7, many implementation units pass TAS with one or more positive FTS results. However, the presence of any FTS positive children in a TAS 2 or TAS 3 indicates possible ongoing transmission. The WHO LF program manager’s manual encourages program managers to conduct follow-up surveys in communities where antigen positive children are found. However, there is currently no published guidance on how this follow-up should be conducted. The goals of this project were to determine the implications of one or more positive FTS results and to provide evidence towards recommendations on how to follow up on these re | Medicine, Health and Life Sciences | FTS; Lymphatic Filariasis |
doi:10.15139/S3/X33NIZ | Bangladesh Maternal Mortality Survey (BMMS) 2016 | <|begin_of_text|><|start_header_id|>system<|end_header_id|> You are a research archivist expert in dataset metadata. Answer the question truthfully. <|eot_id|><|start_header_id|>user<|end_header_id|> Here is the Description of a dataset. Description:'The major objectives of the 2016 Bangladesh Maternal Mortality and Health Care Survey (BMMS) were to provide a nationally representative estimate of the maternal mortality ratio (MMR) for three years preceding the survey (approximately 2014–2016), to identify the causes of maternal deaths, and to assess maternal health seeking behavior indicators and compare them with the BMMS 2010 to see how well the country is progressing toward national and global targets for maternal health since the 2010 survey.The survey was conducted in a nationally representative sample of 306,961 households. In each selected household, ever-married women ages 13 to 49 were interviewed and any deaths among women of reproductive age in the household were investigated using a verbal autopsy instrument, with particular attention to maternal and pregnancy-relate' . Please return only a json list of at most 3 Keywords corresponding to the Description:.<|eot_id|><|start_header_id|>assistant<|end_header_id|> {"Answer" : ["Bangladesh","deaths","maternal","mortality","women"]} <|eot_id|> | Here is the Description of a dataset. Description:'The major objectives of the 2016 Bangladesh Maternal Mortality and Health Care Survey (BMMS) were to provide a nationally representative estimate of the maternal mortality ratio (MMR) for three years preceding the survey (approximately 2014–2016), to identify the causes of maternal deaths, and to assess maternal health seeking behavior indicators and compare them with the BMMS 2010 to see how well the country is progressing toward national and global targets for maternal health since the 2010 survey.The survey was conducted in a nationally representative sample of 306,961 households. In each selected household, ever-married women ages 13 to 49 were interviewed and any deaths among women of reproductive age in the household were investigated using a verbal autopsy instrument, with particular attention to maternal and pregnancy-relate' . Please return only a json list of at most 3 Keywords corresponding to the Description:. | The major objectives of the 2016 Bangladesh Maternal Mortality and Health Care Survey (BMMS) were to provide a nationally representative estimate of the maternal mortality ratio (MMR) for three years preceding the survey (approximately 2014–2016), to identify the causes of maternal deaths, and to assess maternal health seeking behavior indicators and compare them with the BMMS 2010 to see how well the country is progressing toward national and global targets for maternal health since the 2010 survey.The survey was conducted in a nationally representative sample of 306,961 households. In each selected household, ever-married women ages 13 to 49 were interviewed and any deaths among women of reproductive age in the household were investigated using a verbal autopsy instrument, with particular attention to maternal and pregnancy-relate | Medicine, Health and Life Sciences | Bangladesh; deaths; maternal; mortality; women |
doi:10.15139/S3/XSGXUM | Replication Data for: LPG stove and fuel intervention among pregnant women reduce fine particle air pollution exposures in three countries: Pilot results from the HAPIN trial | <|begin_of_text|><|start_header_id|>system<|end_header_id|> You are a research archivist expert in dataset metadata. Answer the question truthfully. <|eot_id|><|start_header_id|>user<|end_header_id|> Here is the Description of a dataset. Description:'Documentation for Liao/Kirby et al data and scripts:Scripts:1. Figure_1.R contains R script to generate figure 1.2. Table_3.R contains R script to generate table 3.3. Table 4+SM_analysis.do contains Stata script for generating table 4 and sensitivity analysis results in supplemental matarials.4. SM_figures_tables.R contains R script for generating table S1 and figure S1 in supplemental materials.Data:1. ExpMod_KAP_v2.csv contains processed kitchen PM2.5 data with covariates, for main analysis2. ExpMod_PEM_v2.csv contains processed personal PM2.5 data with covariates, for main analysis3. Pilot_expousre_data_IN+GT+RW_all.csv contains PM2.5 data only, including PM2.5 duplicates, for sensitivity analysis.4. Table_2.xlsx contains baseline covariates data, for table 2.5. Data dictionary.xlsx contains data dictionary for all above ' . Please return only a json list of at most 3 Keywords corresponding to the Description:.<|eot_id|><|start_header_id|>assistant<|end_header_id|> {"Answer" : ["Clean cooking fuel","Cookstove","Household air pollution"]} <|eot_id|> | Here is the Description of a dataset. Description:'Documentation for Liao/Kirby et al data and scripts:Scripts:1. Figure_1.R contains R script to generate figure 1.2. Table_3.R contains R script to generate table 3.3. Table 4+SM_analysis.do contains Stata script for generating table 4 and sensitivity analysis results in supplemental matarials.4. SM_figures_tables.R contains R script for generating table S1 and figure S1 in supplemental materials.Data:1. ExpMod_KAP_v2.csv contains processed kitchen PM2.5 data with covariates, for main analysis2. ExpMod_PEM_v2.csv contains processed personal PM2.5 data with covariates, for main analysis3. Pilot_expousre_data_IN+GT+RW_all.csv contains PM2.5 data only, including PM2.5 duplicates, for sensitivity analysis.4. Table_2.xlsx contains baseline covariates data, for table 2.5. Data dictionary.xlsx contains data dictionary for all above ' . Please return only a json list of at most 3 Keywords corresponding to the Description:. | Documentation for Liao/Kirby et al data and scripts:Scripts:1. Figure_1.R contains R script to generate figure 1.2. Table_3.R contains R script to generate table 3.3. Table 4+SM_analysis.do contains Stata script for generating table 4 and sensitivity analysis results in supplemental matarials.4. SM_figures_tables.R contains R script for generating table S1 and figure S1 in supplemental materials.Data:1. ExpMod_KAP_v2.csv contains processed kitchen PM2.5 data with covariates, for main analysis2. ExpMod_PEM_v2.csv contains processed personal PM2.5 data with covariates, for main analysis3. Pilot_expousre_data_IN+GT+RW_all.csv contains PM2.5 data only, including PM2.5 duplicates, for sensitivity analysis.4. Table_2.xlsx contains baseline covariates data, for table 2.5. Data dictionary.xlsx contains data dictionary for all above | Medicine, Health and Life Sciences | Clean cooking fuel; Cookstove; Household air pollution |
doi:10.15139/S3/XSZGXR | Supplemental Materials - Metabolomic profiling after a meal shows greater changes and lower metabolic flexibility in cardiometabolic diseases | <|begin_of_text|><|start_header_id|>system<|end_header_id|> You are a research archivist expert in dataset metadata. Answer the question truthfully. <|eot_id|><|start_header_id|>user<|end_header_id|> Here is the Description of a dataset. Description:'Supplemental materials from 'Metabolomic profiling after a meal shows greater changes and lower metabolic flexibility in cardiometabolic diseases.' Supplemental figures 1-4 and supplemental tables 1-3 are included. This study analyzed data that were collected in 2015-2017 as part of the Institute of Nutrition of Central America and Panama (INCAP) Nutrition Trial Cohort Study' . Please return only a json list of at most 3 Keywords corresponding to the Description:.<|eot_id|><|start_header_id|>assistant<|end_header_id|> {"Answer" : ["Cardiometabolic disease","Meal challenge","Metabolic health","Metabolomics","Post-prandial state"]} <|eot_id|> | Here is the Description of a dataset. Description:'Supplemental materials from 'Metabolomic profiling after a meal shows greater changes and lower metabolic flexibility in cardiometabolic diseases.' Supplemental figures 1-4 and supplemental tables 1-3 are included. This study analyzed data that were collected in 2015-2017 as part of the Institute of Nutrition of Central America and Panama (INCAP) Nutrition Trial Cohort Study' . Please return only a json list of at most 3 Keywords corresponding to the Description:. | Supplemental materials from 'Metabolomic profiling after a meal shows greater changes and lower metabolic flexibility in cardiometabolic diseases.' Supplemental figures 1-4 and supplemental tables 1-3 are included. This study analyzed data that were collected in 2015-2017 as part of the Institute of Nutrition of Central America and Panama (INCAP) Nutrition Trial Cohort Study | Medicine, Health and Life Sciences | Cardiometabolic disease; Meal challenge; Metabolic health; Metabolomics; Post-prandial state |
doi:10.15139/S3/YKFNW9 | North Carolina Vital Statistics -- Deaths 2019 | <|begin_of_text|><|start_header_id|>system<|end_header_id|> You are a research archivist expert in dataset metadata. Answer the question truthfully. <|eot_id|><|start_header_id|>user<|end_header_id|> Here is the Description of a dataset. Description:'The North Carolina State Center for Health Services (SCHS) collects yearly vital statistics. The Odum Institute holds vital statistics beginning in 1968 for deaths, marriages and divorce. Public marriage and divorce data are available through 1999 only. Vital statistics for births, fetal deaths, and birth/infant deaths may be obtained directly from SCHS by submitting a request to [email protected] study focuses on deaths in North Carolina in 2019. Death is defined as the permanent disappearance of any evidence of life at any time after live birth. This definition excludes fetal deaths. The data kept for deaths includes the age, race, marital status, and sex of the individual; date, time, cause and location of death; and mode of burial.Minor changes to the files beginning in 2014 reflect the release o' . Please return only a json list of at most 3 Keywords corresponding to the Description:.<|eot_id|><|start_header_id|>assistant<|end_header_id|> {"Answer" : ["Death","Vital statistics"]} <|eot_id|> | Here is the Description of a dataset. Description:'The North Carolina State Center for Health Services (SCHS) collects yearly vital statistics. The Odum Institute holds vital statistics beginning in 1968 for deaths, marriages and divorce. Public marriage and divorce data are available through 1999 only. Vital statistics for births, fetal deaths, and birth/infant deaths may be obtained directly from SCHS by submitting a request to [email protected] study focuses on deaths in North Carolina in 2019. Death is defined as the permanent disappearance of any evidence of life at any time after live birth. This definition excludes fetal deaths. The data kept for deaths includes the age, race, marital status, and sex of the individual; date, time, cause and location of death; and mode of burial.Minor changes to the files beginning in 2014 reflect the release o' . Please return only a json list of at most 3 Keywords corresponding to the Description:. | The North Carolina State Center for Health Services (SCHS) collects yearly vital statistics. The Odum Institute holds vital statistics beginning in 1968 for deaths, marriages and divorce. Public marriage and divorce data are available through 1999 only. Vital statistics for births, fetal deaths, and birth/infant deaths may be obtained directly from SCHS by submitting a request to [email protected] study focuses on deaths in North Carolina in 2019. Death is defined as the permanent disappearance of any evidence of life at any time after live birth. This definition excludes fetal deaths. The data kept for deaths includes the age, race, marital status, and sex of the individual; date, time, cause and location of death; and mode of burial.Minor changes to the files beginning in 2014 reflect the release o | Medicine, Health and Life Sciences | Death; Vital statistics |
doi:10.15139/S3/YKFNW9 | North Carolina Vital Statistics -- Deaths 2019 | <|begin_of_text|><|start_header_id|>system<|end_header_id|> You are a research archivist expert in dataset metadata. Answer the question truthfully. <|eot_id|><|start_header_id|>user<|end_header_id|> Here is the Description of a dataset. Description:'The North Carolina State Center for Health Services (SCHS) collects yearly vital statistics. The Odum Institute holds vital statistics beginning in 1968 for deaths, marriages and divorce. Public marriage and divorce data are available through 1999 only. Vital statistics for births, fetal deaths, and birth/infant deaths may be obtained directly from SCHS by submitting a request to [email protected] study focuses on deaths in North Carolina in 2019. Death is defined as the permanent disappearance of any evidence of life at any time after live birth. This definition excludes fetal deaths. The data kept for deaths includes the age, race, marital status, and sex of the individual; date, time, cause and location of death; and mode of burial.Minor changes to the files beginning in 2014 reflect the release o' . Please return only a json list of at most 3 Keywords corresponding to the Description:.<|eot_id|><|start_header_id|>assistant<|end_header_id|> {"Answer" : ["Death","Vital statistics"]} <|eot_id|> | Here is the Description of a dataset. Description:'The North Carolina State Center for Health Services (SCHS) collects yearly vital statistics. The Odum Institute holds vital statistics beginning in 1968 for deaths, marriages and divorce. Public marriage and divorce data are available through 1999 only. Vital statistics for births, fetal deaths, and birth/infant deaths may be obtained directly from SCHS by submitting a request to [email protected] study focuses on deaths in North Carolina in 2019. Death is defined as the permanent disappearance of any evidence of life at any time after live birth. This definition excludes fetal deaths. The data kept for deaths includes the age, race, marital status, and sex of the individual; date, time, cause and location of death; and mode of burial.Minor changes to the files beginning in 2014 reflect the release o' . Please return only a json list of at most 3 Keywords corresponding to the Description:. | The North Carolina State Center for Health Services (SCHS) collects yearly vital statistics. The Odum Institute holds vital statistics beginning in 1968 for deaths, marriages and divorce. Public marriage and divorce data are available through 1999 only. Vital statistics for births, fetal deaths, and birth/infant deaths may be obtained directly from SCHS by submitting a request to [email protected] study focuses on deaths in North Carolina in 2019. Death is defined as the permanent disappearance of any evidence of life at any time after live birth. This definition excludes fetal deaths. The data kept for deaths includes the age, race, marital status, and sex of the individual; date, time, cause and location of death; and mode of burial.Minor changes to the files beginning in 2014 reflect the release o | Social Sciences | Death; Vital statistics |
doi:10.15139/S3/YPVP7C | NGO Health Service Delivery Project (NHSDP) Endline Rural/Urban Survey 2017 | <|begin_of_text|><|start_header_id|>system<|end_header_id|> You are a research archivist expert in dataset metadata. Answer the question truthfully. <|eot_id|><|start_header_id|>user<|end_header_id|> Here is the Description of a dataset. Description:'The United States Agency for International Development (USAID)/Bangladesh requested an external impact evaluation of the “Nongovernmental Organization (NGO) Health Service Delivery Project” (NHSDP) program that was awarded to Pathfinder International in December 2012. The impact evaluation used a difference-in-difference (DID) strategy to determine program impact. This design requires collecting baseline and endline data in program intervention areas and similar comparison areas, which serve as the counterfactual for the impact evaluation. The 2017 NHSDP endline survey is the last of the two surveys. The main objective of the survey was to measure USAID performance indicators related to health and family planning that the program seeks to improve in program intervention areas and in similar comparison areas (where NHSDP is not in operat' . Please return only a json list of at most 3 Keywords corresponding to the Description:.<|eot_id|><|start_header_id|>assistant<|end_header_id|> {"Answer" : ["Bangladesh","Child health","Family planning","Maternal health"]} <|eot_id|> | Here is the Description of a dataset. Description:'The United States Agency for International Development (USAID)/Bangladesh requested an external impact evaluation of the “Nongovernmental Organization (NGO) Health Service Delivery Project” (NHSDP) program that was awarded to Pathfinder International in December 2012. The impact evaluation used a difference-in-difference (DID) strategy to determine program impact. This design requires collecting baseline and endline data in program intervention areas and similar comparison areas, which serve as the counterfactual for the impact evaluation. The 2017 NHSDP endline survey is the last of the two surveys. The main objective of the survey was to measure USAID performance indicators related to health and family planning that the program seeks to improve in program intervention areas and in similar comparison areas (where NHSDP is not in operat' . Please return only a json list of at most 3 Keywords corresponding to the Description:. | The United States Agency for International Development (USAID)/Bangladesh requested an external impact evaluation of the “Nongovernmental Organization (NGO) Health Service Delivery Project” (NHSDP) program that was awarded to Pathfinder International in December 2012. The impact evaluation used a difference-in-difference (DID) strategy to determine program impact. This design requires collecting baseline and endline data in program intervention areas and similar comparison areas, which serve as the counterfactual for the impact evaluation. The 2017 NHSDP endline survey is the last of the two surveys. The main objective of the survey was to measure USAID performance indicators related to health and family planning that the program seeks to improve in program intervention areas and in similar comparison areas (where NHSDP is not in operat | Medicine, Health and Life Sciences | Bangladesh; Child health; Family planning; Maternal health |
doi:10.15139/S3/YPVP7C | NGO Health Service Delivery Project (NHSDP) Endline Rural/Urban Survey 2017 | <|begin_of_text|><|start_header_id|>system<|end_header_id|> You are a research archivist expert in dataset metadata. Answer the question truthfully. <|eot_id|><|start_header_id|>user<|end_header_id|> Here is the Description of a dataset. Description:'The United States Agency for International Development (USAID)/Bangladesh requested an external impact evaluation of the “Nongovernmental Organization (NGO) Health Service Delivery Project” (NHSDP) program that was awarded to Pathfinder International in December 2012. The impact evaluation used a difference-in-difference (DID) strategy to determine program impact. This design requires collecting baseline and endline data in program intervention areas and similar comparison areas, which serve as the counterfactual for the impact evaluation. The 2017 NHSDP endline survey is the last of the two surveys. The main objective of the survey was to measure USAID performance indicators related to health and family planning that the program seeks to improve in program intervention areas and in similar comparison areas (where NHSDP is not in operat' . Please return only a json list of at most 3 Keywords corresponding to the Description:.<|eot_id|><|start_header_id|>assistant<|end_header_id|> {"Answer" : ["Bangladesh","Child health","Family planning","Maternal health"]} <|eot_id|> | Here is the Description of a dataset. Description:'The United States Agency for International Development (USAID)/Bangladesh requested an external impact evaluation of the “Nongovernmental Organization (NGO) Health Service Delivery Project” (NHSDP) program that was awarded to Pathfinder International in December 2012. The impact evaluation used a difference-in-difference (DID) strategy to determine program impact. This design requires collecting baseline and endline data in program intervention areas and similar comparison areas, which serve as the counterfactual for the impact evaluation. The 2017 NHSDP endline survey is the last of the two surveys. The main objective of the survey was to measure USAID performance indicators related to health and family planning that the program seeks to improve in program intervention areas and in similar comparison areas (where NHSDP is not in operat' . Please return only a json list of at most 3 Keywords corresponding to the Description:. | The United States Agency for International Development (USAID)/Bangladesh requested an external impact evaluation of the “Nongovernmental Organization (NGO) Health Service Delivery Project” (NHSDP) program that was awarded to Pathfinder International in December 2012. The impact evaluation used a difference-in-difference (DID) strategy to determine program impact. This design requires collecting baseline and endline data in program intervention areas and similar comparison areas, which serve as the counterfactual for the impact evaluation. The 2017 NHSDP endline survey is the last of the two surveys. The main objective of the survey was to measure USAID performance indicators related to health and family planning that the program seeks to improve in program intervention areas and in similar comparison areas (where NHSDP is not in operat | Social Sciences | Bangladesh; Child health; Family planning; Maternal health |
doi:10.15139/S3/Z6FUWF | District Mapping Onchocerciasis, Lymphatic Filariasis, and Loiasis in Gabon | <|begin_of_text|><|start_header_id|>system<|end_header_id|> You are a research archivist expert in dataset metadata. Answer the question truthfully. <|eot_id|><|start_header_id|>user<|end_header_id|> Here is the Description of a dataset. Description:'The purpose of the study was to define a cost-effective and accurate method to map ivermectin-naïve districts for Onchocerciasis, Lymphatic Filariasis and Loiasis and identify districts eligible for safe treatment with ivermectin MDA. The study aimed primarily to validate a statistical model calibrated to determine whether community-level prevalence of Loa infection of >20,000 mf/mL is less than 1% in a community by comparing results of the model to results of a community-level random sample prevalence assessment' . Please return only a json list of at most 3 Keywords corresponding to the Description:.<|eot_id|><|start_header_id|>assistant<|end_header_id|> {"Answer" : ["Loa loa antibody rapid test","LoaScope","Loiasis","Lymphatic Filariasis","Onchocerciasis","Oncho/LF IgG4 biplex RDT"]} <|eot_id|> | Here is the Description of a dataset. Description:'The purpose of the study was to define a cost-effective and accurate method to map ivermectin-naïve districts for Onchocerciasis, Lymphatic Filariasis and Loiasis and identify districts eligible for safe treatment with ivermectin MDA. The study aimed primarily to validate a statistical model calibrated to determine whether community-level prevalence of Loa infection of >20,000 mf/mL is less than 1% in a community by comparing results of the model to results of a community-level random sample prevalence assessment' . Please return only a json list of at most 3 Keywords corresponding to the Description:. | The purpose of the study was to define a cost-effective and accurate method to map ivermectin-naïve districts for Onchocerciasis, Lymphatic Filariasis and Loiasis and identify districts eligible for safe treatment with ivermectin MDA. The study aimed primarily to validate a statistical model calibrated to determine whether community-level prevalence of Loa infection of >20,000 mf/mL is less than 1% in a community by comparing results of the model to results of a community-level random sample prevalence assessment | Medicine, Health and Life Sciences | Loa loa antibody rapid test; LoaScope; Loiasis; Lymphatic Filariasis; Onchocerciasis; Oncho/LF IgG4 biplex RDT |
doi:10.15139/S3/ZHWV4T | A Study of the Local Capacity Initiative in Uganda: Longitudinal Survey of Public Officials | <|begin_of_text|><|start_header_id|>system<|end_header_id|> You are a research archivist expert in dataset metadata. Answer the question truthfully. <|eot_id|><|start_header_id|>user<|end_header_id|> Here is the Description of a dataset. Description:'The primary purpose of the Local Capacity Initiative (LCI) evaluation, including the Uganda case study, was to foster learning about how policy advocacy activities can contribute to increased access to quality HIV services for key populations and vulnerable groups. Public officials who were targeted by the LCI intervention were included in a survey. The goal of the survey was to assess the degree to which LCI activities have served as a resource to public officials, as well as their knowledge and attitudes towards SWs, MSM, and HIV service provision for these groups. A sampe of public officials were invited to participate at the national and district level. The public officials who were reached in 2016 form a panel that was followed up and re-surveyed in 2018' . Please return only a json list of at most 3 Keywords corresponding to the Description:.<|eot_id|><|start_header_id|>assistant<|end_header_id|> {"Answer" : ["HIV","Key populations","MSM","Public officials","Uganda","Vulnerable groups"]} <|eot_id|> | Here is the Description of a dataset. Description:'The primary purpose of the Local Capacity Initiative (LCI) evaluation, including the Uganda case study, was to foster learning about how policy advocacy activities can contribute to increased access to quality HIV services for key populations and vulnerable groups. Public officials who were targeted by the LCI intervention were included in a survey. The goal of the survey was to assess the degree to which LCI activities have served as a resource to public officials, as well as their knowledge and attitudes towards SWs, MSM, and HIV service provision for these groups. A sampe of public officials were invited to participate at the national and district level. The public officials who were reached in 2016 form a panel that was followed up and re-surveyed in 2018' . Please return only a json list of at most 3 Keywords corresponding to the Description:. | The primary purpose of the Local Capacity Initiative (LCI) evaluation, including the Uganda case study, was to foster learning about how policy advocacy activities can contribute to increased access to quality HIV services for key populations and vulnerable groups. Public officials who were targeted by the LCI intervention were included in a survey. The goal of the survey was to assess the degree to which LCI activities have served as a resource to public officials, as well as their knowledge and attitudes towards SWs, MSM, and HIV service provision for these groups. A sampe of public officials were invited to participate at the national and district level. The public officials who were reached in 2016 form a panel that was followed up and re-surveyed in 2018 | Medicine, Health and Life Sciences | HIV; Key populations; MSM; Public officials; Uganda; Vulnerable groups |
doi:10.15139/S3/ZK60QH | The East Africa Cross-Border Integrated Health Study (2016-2017) | <|begin_of_text|><|start_header_id|>system<|end_header_id|> You are a research archivist expert in dataset metadata. Answer the question truthfully. <|eot_id|><|start_header_id|>user<|end_header_id|> Here is the Description of a dataset. Description:'These data were collected for a cross-sectional study describing the health status and behaviors of mobile and vulnerable populations living in or traveling through 12 cross-border sites in the East African countries of Kenya, Rwanda, Tanzania, and Uganda. The Priorities for Local AIDS Control Efforts (PLACE) method was used to conduct interviews and HIV testing among people working or socializing at public venues in these cross-border sites' . Please return only a json list of at most 3 Keywords corresponding to the Description:.<|eot_id|><|start_header_id|>assistant<|end_header_id|> {"Answer" : ["HIV, East Africa, HIV prevention, HIV testing, epidemiology, survey"]} <|eot_id|> | Here is the Description of a dataset. Description:'These data were collected for a cross-sectional study describing the health status and behaviors of mobile and vulnerable populations living in or traveling through 12 cross-border sites in the East African countries of Kenya, Rwanda, Tanzania, and Uganda. The Priorities for Local AIDS Control Efforts (PLACE) method was used to conduct interviews and HIV testing among people working or socializing at public venues in these cross-border sites' . Please return only a json list of at most 3 Keywords corresponding to the Description:. | These data were collected for a cross-sectional study describing the health status and behaviors of mobile and vulnerable populations living in or traveling through 12 cross-border sites in the East African countries of Kenya, Rwanda, Tanzania, and Uganda. The Priorities for Local AIDS Control Efforts (PLACE) method was used to conduct interviews and HIV testing among people working or socializing at public venues in these cross-border sites | Medicine, Health and Life Sciences | HIV, East Africa, HIV prevention, HIV testing, epidemiology, survey |
doi:10.15139/S3/ZNNGMH | A Study of the Local Capacity Initiative in Uganda: Longitudinal Survey of Public Officials | <|begin_of_text|><|start_header_id|>system<|end_header_id|> You are a research archivist expert in dataset metadata. Answer the question truthfully. <|eot_id|><|start_header_id|>user<|end_header_id|> Here is the Description of a dataset. Description:'The primary purpose of the Local Capacity Initiative (LCI) evaluation, including the Uganda case study, was to foster learning about how policy advocacy activities can contribute to increased access to quality HIV services for key populations and vulnerable groups. Public officials who were targeted by the LCI intervention were included in a survey. The goal of the survey was to assess the degree to which LCI activities have served as a resource to public officials, as well as their knowledge and attitudes towards SWs, MSM, and HIV service provision for these groups. A sampe of public officials were invited to participate at the national and district level. The public officials who were reached in 2016 form a panel that was followed up and re-surveyed in 2018' . Please return only a json list of at most 3 Keywords corresponding to the Description:.<|eot_id|><|start_header_id|>assistant<|end_header_id|> {"Answer" : ["HIV","Key populations","MSM","Public officials","Uganda","Vulnerable groups"]} <|eot_id|> | Here is the Description of a dataset. Description:'The primary purpose of the Local Capacity Initiative (LCI) evaluation, including the Uganda case study, was to foster learning about how policy advocacy activities can contribute to increased access to quality HIV services for key populations and vulnerable groups. Public officials who were targeted by the LCI intervention were included in a survey. The goal of the survey was to assess the degree to which LCI activities have served as a resource to public officials, as well as their knowledge and attitudes towards SWs, MSM, and HIV service provision for these groups. A sampe of public officials were invited to participate at the national and district level. The public officials who were reached in 2016 form a panel that was followed up and re-surveyed in 2018' . Please return only a json list of at most 3 Keywords corresponding to the Description:. | The primary purpose of the Local Capacity Initiative (LCI) evaluation, including the Uganda case study, was to foster learning about how policy advocacy activities can contribute to increased access to quality HIV services for key populations and vulnerable groups. Public officials who were targeted by the LCI intervention were included in a survey. The goal of the survey was to assess the degree to which LCI activities have served as a resource to public officials, as well as their knowledge and attitudes towards SWs, MSM, and HIV service provision for these groups. A sampe of public officials were invited to participate at the national and district level. The public officials who were reached in 2016 form a panel that was followed up and re-surveyed in 2018 | Medicine, Health and Life Sciences | HIV; Key populations; MSM; Public officials; Uganda; Vulnerable groups |
doi:10.15139/S3/ZTN9EY | Mayer Hashi II Endline Survey 2017 | <|begin_of_text|><|start_header_id|>system<|end_header_id|> You are a research archivist expert in dataset metadata. Answer the question truthfully. <|eot_id|><|start_header_id|>user<|end_header_id|> Here is the Description of a dataset. Description:'An external impact evaluation of the Mayer Hashi Phase II (MH-II) project was requested by the U.S. Agency for International Development (USAID)/Bangladesh. MH-II, which is a follow-on project to the previous Mayer Hashi (MH-I) project, was initially awarded to EngenderHealth for the period October 2013 to September 2017, but was subsequently extended to September 2018. The 2017 Endline Mayer Hashi Phase II Evaluation Survey is the last of two surveys to evaluate the impact of MH-II in increasing the use of effective family planning (FP) and reproductive health services among the population in Bangladesh' . Please return only a json list of at most 3 Keywords corresponding to the Description:.<|eot_id|><|start_header_id|>assistant<|end_header_id|> {"Answer" : ["Bangladesh","Family planning","Reproductive health services"]} <|eot_id|> | Here is the Description of a dataset. Description:'An external impact evaluation of the Mayer Hashi Phase II (MH-II) project was requested by the U.S. Agency for International Development (USAID)/Bangladesh. MH-II, which is a follow-on project to the previous Mayer Hashi (MH-I) project, was initially awarded to EngenderHealth for the period October 2013 to September 2017, but was subsequently extended to September 2018. The 2017 Endline Mayer Hashi Phase II Evaluation Survey is the last of two surveys to evaluate the impact of MH-II in increasing the use of effective family planning (FP) and reproductive health services among the population in Bangladesh' . Please return only a json list of at most 3 Keywords corresponding to the Description:. | An external impact evaluation of the Mayer Hashi Phase II (MH-II) project was requested by the U.S. Agency for International Development (USAID)/Bangladesh. MH-II, which is a follow-on project to the previous Mayer Hashi (MH-I) project, was initially awarded to EngenderHealth for the period October 2013 to September 2017, but was subsequently extended to September 2018. The 2017 Endline Mayer Hashi Phase II Evaluation Survey is the last of two surveys to evaluate the impact of MH-II in increasing the use of effective family planning (FP) and reproductive health services among the population in Bangladesh | Medicine, Health and Life Sciences | Bangladesh; Family planning; Reproductive health services |
doi:10.15139/S3/ZTN9EY | Mayer Hashi II Endline Survey 2017 | <|begin_of_text|><|start_header_id|>system<|end_header_id|> You are a research archivist expert in dataset metadata. Answer the question truthfully. <|eot_id|><|start_header_id|>user<|end_header_id|> Here is the Description of a dataset. Description:'An external impact evaluation of the Mayer Hashi Phase II (MH-II) project was requested by the U.S. Agency for International Development (USAID)/Bangladesh. MH-II, which is a follow-on project to the previous Mayer Hashi (MH-I) project, was initially awarded to EngenderHealth for the period October 2013 to September 2017, but was subsequently extended to September 2018. The 2017 Endline Mayer Hashi Phase II Evaluation Survey is the last of two surveys to evaluate the impact of MH-II in increasing the use of effective family planning (FP) and reproductive health services among the population in Bangladesh' . Please return only a json list of at most 3 Keywords corresponding to the Description:.<|eot_id|><|start_header_id|>assistant<|end_header_id|> {"Answer" : ["Bangladesh","Family planning","Reproductive health services"]} <|eot_id|> | Here is the Description of a dataset. Description:'An external impact evaluation of the Mayer Hashi Phase II (MH-II) project was requested by the U.S. Agency for International Development (USAID)/Bangladesh. MH-II, which is a follow-on project to the previous Mayer Hashi (MH-I) project, was initially awarded to EngenderHealth for the period October 2013 to September 2017, but was subsequently extended to September 2018. The 2017 Endline Mayer Hashi Phase II Evaluation Survey is the last of two surveys to evaluate the impact of MH-II in increasing the use of effective family planning (FP) and reproductive health services among the population in Bangladesh' . Please return only a json list of at most 3 Keywords corresponding to the Description:. | An external impact evaluation of the Mayer Hashi Phase II (MH-II) project was requested by the U.S. Agency for International Development (USAID)/Bangladesh. MH-II, which is a follow-on project to the previous Mayer Hashi (MH-I) project, was initially awarded to EngenderHealth for the period October 2013 to September 2017, but was subsequently extended to September 2018. The 2017 Endline Mayer Hashi Phase II Evaluation Survey is the last of two surveys to evaluate the impact of MH-II in increasing the use of effective family planning (FP) and reproductive health services among the population in Bangladesh | Social Sciences | Bangladesh; Family planning; Reproductive health services |
doi:10.18130/V3/7UAPHU | Data Associated with the Publication: Vital Sign Metrics of VLBW Infants in Three NICUs: Implications for Predictive Algorithms | <|begin_of_text|><|start_header_id|>system<|end_header_id|> You are a research archivist expert in dataset metadata. Answer the question truthfully. <|eot_id|><|start_header_id|>user<|end_header_id|> Here is the Description of a dataset. Description:'This repository contains the dataset and code for the manuscript:Zimmet AM, Sullivan BA, Fairchild KD, Moorman JR, Isler JR, Wallman-Stokes AW, Sahni R, Vesoulis ZA, Ratcliffe SJ, & Lake DE. Vital Sign Metrics of VLBW Infants in Three NICUs: Implications for Predictive Algorithms. Pediatric Research 2021. https://doi.org/10.1038/s41390-021-01428-3. EXPLANATION OF DATA FILES AND CODE To understand all of the included data files and to tell you which key files do what, review the ReadMe_VitalSignMetrics_20200226.txt file. HOW TO USE THE CODE After reviewing ReadMe_VitalSignMetrics_20200226.txt file, follow the entire code progression from raw data (the raw data itself could not be published), to summary data (included in this repository), through figure generation, via the' . Please return only a json list of at most 3 Keywords corresponding to the Description:.<|eot_id|><|start_header_id|>assistant<|end_header_id|> {"Answer" : ["algorithm","continuous monitoring","neonate","neonatology","newborn","predictive analytics","prematurity","preterm infants"]} <|eot_id|> | Here is the Description of a dataset. Description:'This repository contains the dataset and code for the manuscript:Zimmet AM, Sullivan BA, Fairchild KD, Moorman JR, Isler JR, Wallman-Stokes AW, Sahni R, Vesoulis ZA, Ratcliffe SJ, & Lake DE. Vital Sign Metrics of VLBW Infants in Three NICUs: Implications for Predictive Algorithms. Pediatric Research 2021. https://doi.org/10.1038/s41390-021-01428-3. EXPLANATION OF DATA FILES AND CODE To understand all of the included data files and to tell you which key files do what, review the ReadMe_VitalSignMetrics_20200226.txt file. HOW TO USE THE CODE After reviewing ReadMe_VitalSignMetrics_20200226.txt file, follow the entire code progression from raw data (the raw data itself could not be published), to summary data (included in this repository), through figure generation, via the' . Please return only a json list of at most 3 Keywords corresponding to the Description:. | This repository contains the dataset and code for the manuscript:Zimmet AM, Sullivan BA, Fairchild KD, Moorman JR, Isler JR, Wallman-Stokes AW, Sahni R, Vesoulis ZA, Ratcliffe SJ, & Lake DE. Vital Sign Metrics of VLBW Infants in Three NICUs: Implications for Predictive Algorithms. Pediatric Research 2021. https://doi.org/10.1038/s41390-021-01428-3. EXPLANATION OF DATA FILES AND CODE To understand all of the included data files and to tell you which key files do what, review the ReadMe_VitalSignMetrics_20200226.txt file. HOW TO USE THE CODE After reviewing ReadMe_VitalSignMetrics_20200226.txt file, follow the entire code progression from raw data (the raw data itself could not be published), to summary data (included in this repository), through figure generation, via the | Medicine, Health and Life Sciences | algorithm; continuous monitoring; neonate; neonatology; newborn; predictive analytics; prematurity; preterm infants |
doi:10.18130/V3/YQLJ5W | Baidu mobility data for January through April, 2020 | <|begin_of_text|><|start_header_id|>system<|end_header_id|> You are a research archivist expert in dataset metadata. Answer the question truthfully. <|eot_id|><|start_header_id|>user<|end_header_id|> Here is the Description of a dataset. Description:'This archive contains mobility data made public by Baidu and scraped from their qiangxi.baidu.com web site in February, March, and April, 2020. We have reformatted the data into a more easily computable form, comma-separated value (csv) files providing the full origin-destination matrix for each day.We are publishing this reformatted version for research purposes under Article 22 of the Copyright Law of the People's Republic of China (https://wipolex.wipo.int/en/text/466268). We make no representation as to the suitability of the data for any purpose, but nevertheless hope that it may be useful for researchers trying to calibrate models of 2019-ncov. We wish to thank Baidu especially for making these valuable data available and encourage them to continue to do so. Thanks also to Chunhong Mao for making us aware of this data sourc' . Please return only a json list of at most 3 Keywords corresponding to the Description:.<|eot_id|><|start_header_id|>assistant<|end_header_id|> {"Answer" : ["2019-ncov","Baidu","mobility","Wuhan"]} <|eot_id|> | Here is the Description of a dataset. Description:'This archive contains mobility data made public by Baidu and scraped from their qiangxi.baidu.com web site in February, March, and April, 2020. We have reformatted the data into a more easily computable form, comma-separated value (csv) files providing the full origin-destination matrix for each day.We are publishing this reformatted version for research purposes under Article 22 of the Copyright Law of the People's Republic of China (https://wipolex.wipo.int/en/text/466268). We make no representation as to the suitability of the data for any purpose, but nevertheless hope that it may be useful for researchers trying to calibrate models of 2019-ncov. We wish to thank Baidu especially for making these valuable data available and encourage them to continue to do so. Thanks also to Chunhong Mao for making us aware of this data sourc' . Please return only a json list of at most 3 Keywords corresponding to the Description:. | This archive contains mobility data made public by Baidu and scraped from their qiangxi.baidu.com web site in February, March, and April, 2020. We have reformatted the data into a more easily computable form, comma-separated value (csv) files providing the full origin-destination matrix for each day.We are publishing this reformatted version for research purposes under Article 22 of the Copyright Law of the People's Republic of China (https://wipolex.wipo.int/en/text/466268). We make no representation as to the suitability of the data for any purpose, but nevertheless hope that it may be useful for researchers trying to calibrate models of 2019-ncov. We wish to thank Baidu especially for making these valuable data available and encourage them to continue to do so. Thanks also to Chunhong Mao for making us aware of this data sourc | Computer and Information Science | 2019-ncov; Baidu; mobility; Wuhan |
doi:10.18130/V3/YQLJ5W | Baidu mobility data for January through April, 2020 | <|begin_of_text|><|start_header_id|>system<|end_header_id|> You are a research archivist expert in dataset metadata. Answer the question truthfully. <|eot_id|><|start_header_id|>user<|end_header_id|> Here is the Description of a dataset. Description:'This archive contains mobility data made public by Baidu and scraped from their qiangxi.baidu.com web site in February, March, and April, 2020. We have reformatted the data into a more easily computable form, comma-separated value (csv) files providing the full origin-destination matrix for each day.We are publishing this reformatted version for research purposes under Article 22 of the Copyright Law of the People's Republic of China (https://wipolex.wipo.int/en/text/466268). We make no representation as to the suitability of the data for any purpose, but nevertheless hope that it may be useful for researchers trying to calibrate models of 2019-ncov. We wish to thank Baidu especially for making these valuable data available and encourage them to continue to do so. Thanks also to Chunhong Mao for making us aware of this data sourc' . Please return only a json list of at most 3 Keywords corresponding to the Description:.<|eot_id|><|start_header_id|>assistant<|end_header_id|> {"Answer" : ["2019-ncov","Baidu","mobility","Wuhan"]} <|eot_id|> | Here is the Description of a dataset. Description:'This archive contains mobility data made public by Baidu and scraped from their qiangxi.baidu.com web site in February, March, and April, 2020. We have reformatted the data into a more easily computable form, comma-separated value (csv) files providing the full origin-destination matrix for each day.We are publishing this reformatted version for research purposes under Article 22 of the Copyright Law of the People's Republic of China (https://wipolex.wipo.int/en/text/466268). We make no representation as to the suitability of the data for any purpose, but nevertheless hope that it may be useful for researchers trying to calibrate models of 2019-ncov. We wish to thank Baidu especially for making these valuable data available and encourage them to continue to do so. Thanks also to Chunhong Mao for making us aware of this data sourc' . Please return only a json list of at most 3 Keywords corresponding to the Description:. | This archive contains mobility data made public by Baidu and scraped from their qiangxi.baidu.com web site in February, March, and April, 2020. We have reformatted the data into a more easily computable form, comma-separated value (csv) files providing the full origin-destination matrix for each day.We are publishing this reformatted version for research purposes under Article 22 of the Copyright Law of the People's Republic of China (https://wipolex.wipo.int/en/text/466268). We make no representation as to the suitability of the data for any purpose, but nevertheless hope that it may be useful for researchers trying to calibrate models of 2019-ncov. We wish to thank Baidu especially for making these valuable data available and encourage them to continue to do so. Thanks also to Chunhong Mao for making us aware of this data sourc | Mathematical Sciences | 2019-ncov; Baidu; mobility; Wuhan |
doi:10.18130/V3/YQLJ5W | Baidu mobility data for January through April, 2020 | <|begin_of_text|><|start_header_id|>system<|end_header_id|> You are a research archivist expert in dataset metadata. Answer the question truthfully. <|eot_id|><|start_header_id|>user<|end_header_id|> Here is the Description of a dataset. Description:'This archive contains mobility data made public by Baidu and scraped from their qiangxi.baidu.com web site in February, March, and April, 2020. We have reformatted the data into a more easily computable form, comma-separated value (csv) files providing the full origin-destination matrix for each day.We are publishing this reformatted version for research purposes under Article 22 of the Copyright Law of the People's Republic of China (https://wipolex.wipo.int/en/text/466268). We make no representation as to the suitability of the data for any purpose, but nevertheless hope that it may be useful for researchers trying to calibrate models of 2019-ncov. We wish to thank Baidu especially for making these valuable data available and encourage them to continue to do so. Thanks also to Chunhong Mao for making us aware of this data sourc' . Please return only a json list of at most 3 Keywords corresponding to the Description:.<|eot_id|><|start_header_id|>assistant<|end_header_id|> {"Answer" : ["2019-ncov","Baidu","mobility","Wuhan"]} <|eot_id|> | Here is the Description of a dataset. Description:'This archive contains mobility data made public by Baidu and scraped from their qiangxi.baidu.com web site in February, March, and April, 2020. We have reformatted the data into a more easily computable form, comma-separated value (csv) files providing the full origin-destination matrix for each day.We are publishing this reformatted version for research purposes under Article 22 of the Copyright Law of the People's Republic of China (https://wipolex.wipo.int/en/text/466268). We make no representation as to the suitability of the data for any purpose, but nevertheless hope that it may be useful for researchers trying to calibrate models of 2019-ncov. We wish to thank Baidu especially for making these valuable data available and encourage them to continue to do so. Thanks also to Chunhong Mao for making us aware of this data sourc' . Please return only a json list of at most 3 Keywords corresponding to the Description:. | This archive contains mobility data made public by Baidu and scraped from their qiangxi.baidu.com web site in February, March, and April, 2020. We have reformatted the data into a more easily computable form, comma-separated value (csv) files providing the full origin-destination matrix for each day.We are publishing this reformatted version for research purposes under Article 22 of the Copyright Law of the People's Republic of China (https://wipolex.wipo.int/en/text/466268). We make no representation as to the suitability of the data for any purpose, but nevertheless hope that it may be useful for researchers trying to calibrate models of 2019-ncov. We wish to thank Baidu especially for making these valuable data available and encourage them to continue to do so. Thanks also to Chunhong Mao for making us aware of this data sourc | Medicine, Health and Life Sciences | 2019-ncov; Baidu; mobility; Wuhan |
doi:10.18710/0C1SP5 | Video recordings of spawning behavior of Arctic charr; date: 2016-09-23; spawning ground: 3; time: morning; camera no: 1 | <|begin_of_text|><|start_header_id|>system<|end_header_id|> You are a research archivist expert in dataset metadata. Answer the question truthfully. <|eot_id|><|start_header_id|>user<|end_header_id|> Here is the Description of a dataset. Description:'This dataset contains video recordings of spawning behavior of Arctic charr (Salvelinus alpinus) in Lake Fjellfrøsvatnet (69°08′N 19°34′E), Troms, Northern Norway. The recordings were made with camera no. 1 at spawning ground 3 in the morning of 23 September 2016.A description of the data structure and format is gathered in the documentation dataset: Egeland, Torvald B.; Folstad, Ivar; Nordeide, Jarle Tryti, 2021, 'Documentation of the Spawning behavior of Arctic charr video collection', DataverseNO, https://doi.org/10.18710/VIQB0BThis dataset is part of a larger collection: Egeland, Torvald B.; Folstad, Ivar; Nordeide, Jarle Tryti, 2021, 'The Spawning behavior of Arctic charr video collection'. DataverseNO. https://doi.org/10.18710/HTM6-F146.</p' . Please return only a json list of at most 3 Keywords corresponding to the Description:.<|eot_id|><|start_header_id|>assistant<|end_header_id|> {"Answer" : ["Arctic charr","courtship","egg predation","female choice","filial cannibalism","gamete synchrony","male-male competition","mate guarding","protective behaviour","Salvelinus alpinus","sexual selection","spawning behavior","sperm competition","vibrational communication"]} <|eot_id|> | Here is the Description of a dataset. Description:'This dataset contains video recordings of spawning behavior of Arctic charr (Salvelinus alpinus) in Lake Fjellfrøsvatnet (69°08′N 19°34′E), Troms, Northern Norway. The recordings were made with camera no. 1 at spawning ground 3 in the morning of 23 September 2016.A description of the data structure and format is gathered in the documentation dataset: Egeland, Torvald B.; Folstad, Ivar; Nordeide, Jarle Tryti, 2021, 'Documentation of the Spawning behavior of Arctic charr video collection', DataverseNO, https://doi.org/10.18710/VIQB0BThis dataset is part of a larger collection: Egeland, Torvald B.; Folstad, Ivar; Nordeide, Jarle Tryti, 2021, 'The Spawning behavior of Arctic charr video collection'. DataverseNO. https://doi.org/10.18710/HTM6-F146.</p' . Please return only a json list of at most 3 Keywords corresponding to the Description:. | This dataset contains video recordings of spawning behavior of Arctic charr (Salvelinus alpinus) in Lake Fjellfrøsvatnet (69°08′N 19°34′E), Troms, Northern Norway. The recordings were made with camera no. 1 at spawning ground 3 in the morning of 23 September 2016.A description of the data structure and format is gathered in the documentation dataset: Egeland, Torvald B.; Folstad, Ivar; Nordeide, Jarle Tryti, 2021, 'Documentation of the Spawning behavior of Arctic charr video collection', DataverseNO, https://doi.org/10.18710/VIQB0BThis dataset is part of a larger collection: Egeland, Torvald B.; Folstad, Ivar; Nordeide, Jarle Tryti, 2021, 'The Spawning behavior of Arctic charr video collection'. DataverseNO. https://doi.org/10.18710/HTM6-F146.</p | Medicine, Health and Life Sciences | Arctic charr; courtship; egg predation; female choice; filial cannibalism; gamete synchrony; male-male competition; mate guarding; protective behaviour; Salvelinus alpinus; sexual selection; spawning behavior; sperm competition; vibrational communication |
doi:10.18710/0C4PBP | Video recordings of spawning behavior of Arctic charr; date: 2016-09-23; spawning ground: 3; time: morning; camera no: 3 | <|begin_of_text|><|start_header_id|>system<|end_header_id|> You are a research archivist expert in dataset metadata. Answer the question truthfully. <|eot_id|><|start_header_id|>user<|end_header_id|> Here is the Description of a dataset. Description:'This dataset contains video recordings of spawning behavior of Arctic charr (Salvelinus alpinus) in Lake Fjellfrøsvatnet (69°08′N 19°34′E), Troms, Northern Norway. The recordings were made with camera no. 3 at spawning ground 3 in the morning of 23 September 2016.A description of the data structure and format is gathered in the documentation dataset: Egeland, Torvald B.; Folstad, Ivar; Nordeide, Jarle Tryti, 2021, 'Documentation of the Spawning behavior of Arctic charr video collection', DataverseNO, https://doi.org/10.18710/VIQB0BThis dataset is part of a larger collection: Egeland, Torvald B.; Folstad, Ivar; Nordeide, Jarle Tryti, 2021, 'The Spawning behavior of Arctic charr video collection'. DataverseNO. https://doi.org/10.18710/HTM6-F146.</p' . Please return only a json list of at most 3 Keywords corresponding to the Description:.<|eot_id|><|start_header_id|>assistant<|end_header_id|> {"Answer" : ["Arctic charr","courtship","egg predation","female choice","filial cannibalism","gamete synchrony","male-male competition","mate guarding","protective behaviour","Salvelinus alpinus","sexual selection","spawning behavior","sperm competition","vibrational communication"]} <|eot_id|> | Here is the Description of a dataset. Description:'This dataset contains video recordings of spawning behavior of Arctic charr (Salvelinus alpinus) in Lake Fjellfrøsvatnet (69°08′N 19°34′E), Troms, Northern Norway. The recordings were made with camera no. 3 at spawning ground 3 in the morning of 23 September 2016.A description of the data structure and format is gathered in the documentation dataset: Egeland, Torvald B.; Folstad, Ivar; Nordeide, Jarle Tryti, 2021, 'Documentation of the Spawning behavior of Arctic charr video collection', DataverseNO, https://doi.org/10.18710/VIQB0BThis dataset is part of a larger collection: Egeland, Torvald B.; Folstad, Ivar; Nordeide, Jarle Tryti, 2021, 'The Spawning behavior of Arctic charr video collection'. DataverseNO. https://doi.org/10.18710/HTM6-F146.</p' . Please return only a json list of at most 3 Keywords corresponding to the Description:. | This dataset contains video recordings of spawning behavior of Arctic charr (Salvelinus alpinus) in Lake Fjellfrøsvatnet (69°08′N 19°34′E), Troms, Northern Norway. The recordings were made with camera no. 3 at spawning ground 3 in the morning of 23 September 2016.A description of the data structure and format is gathered in the documentation dataset: Egeland, Torvald B.; Folstad, Ivar; Nordeide, Jarle Tryti, 2021, 'Documentation of the Spawning behavior of Arctic charr video collection', DataverseNO, https://doi.org/10.18710/VIQB0BThis dataset is part of a larger collection: Egeland, Torvald B.; Folstad, Ivar; Nordeide, Jarle Tryti, 2021, 'The Spawning behavior of Arctic charr video collection'. DataverseNO. https://doi.org/10.18710/HTM6-F146.</p | Medicine, Health and Life Sciences | Arctic charr; courtship; egg predation; female choice; filial cannibalism; gamete synchrony; male-male competition; mate guarding; protective behaviour; Salvelinus alpinus; sexual selection; spawning behavior; sperm competition; vibrational communication |
doi:10.18710/0H9FPI | Video recordings of spawning behavior of Arctic charr; date: 2016-09-15; spawning ground: 3; time: morning; camera no: 2 | <|begin_of_text|><|start_header_id|>system<|end_header_id|> You are a research archivist expert in dataset metadata. Answer the question truthfully. <|eot_id|><|start_header_id|>user<|end_header_id|> Here is the Description of a dataset. Description:'This dataset contains video recordings of spawning behavior of Arctic charr (Salvelinus alpinus) in Lake Fjellfrøsvatnet (69°08′N 19°34′E), Troms, Northern Norway. The recordings were made with camera no. 2 at spawning ground 3 in the morning of 15 September 2016.A description of the data structure and format is gathered in the documentation dataset: Egeland, Torvald B.; Folstad, Ivar; Nordeide, Jarle Tryti, 2021, 'Documentation of the Spawning behavior of Arctic charr video collection', DataverseNO, https://doi.org/10.18710/VIQB0BThis dataset is part of a larger collection: Egeland, Torvald B.; Folstad, Ivar; Nordeide, Jarle Tryti, 2021, 'The Spawning behavior of Arctic charr video collection'. DataverseNO. https://doi.org/10.18710/HTM6-F146.</p' . Please return only a json list of at most 3 Keywords corresponding to the Description:.<|eot_id|><|start_header_id|>assistant<|end_header_id|> {"Answer" : ["Arctic charr","courtship","egg predation","female choice","filial cannibalism","gamete synchrony","male-male competition","mate guarding","protective behaviour","Salvelinus alpinus","sexual selection","spawning behavior","sperm competition","vibrational communication"]} <|eot_id|> | Here is the Description of a dataset. Description:'This dataset contains video recordings of spawning behavior of Arctic charr (Salvelinus alpinus) in Lake Fjellfrøsvatnet (69°08′N 19°34′E), Troms, Northern Norway. The recordings were made with camera no. 2 at spawning ground 3 in the morning of 15 September 2016.A description of the data structure and format is gathered in the documentation dataset: Egeland, Torvald B.; Folstad, Ivar; Nordeide, Jarle Tryti, 2021, 'Documentation of the Spawning behavior of Arctic charr video collection', DataverseNO, https://doi.org/10.18710/VIQB0BThis dataset is part of a larger collection: Egeland, Torvald B.; Folstad, Ivar; Nordeide, Jarle Tryti, 2021, 'The Spawning behavior of Arctic charr video collection'. DataverseNO. https://doi.org/10.18710/HTM6-F146.</p' . Please return only a json list of at most 3 Keywords corresponding to the Description:. | This dataset contains video recordings of spawning behavior of Arctic charr (Salvelinus alpinus) in Lake Fjellfrøsvatnet (69°08′N 19°34′E), Troms, Northern Norway. The recordings were made with camera no. 2 at spawning ground 3 in the morning of 15 September 2016.A description of the data structure and format is gathered in the documentation dataset: Egeland, Torvald B.; Folstad, Ivar; Nordeide, Jarle Tryti, 2021, 'Documentation of the Spawning behavior of Arctic charr video collection', DataverseNO, https://doi.org/10.18710/VIQB0BThis dataset is part of a larger collection: Egeland, Torvald B.; Folstad, Ivar; Nordeide, Jarle Tryti, 2021, 'The Spawning behavior of Arctic charr video collection'. DataverseNO. https://doi.org/10.18710/HTM6-F146.</p | Medicine, Health and Life Sciences | Arctic charr; courtship; egg predation; female choice; filial cannibalism; gamete synchrony; male-male competition; mate guarding; protective behaviour; Salvelinus alpinus; sexual selection; spawning behavior; sperm competition; vibrational communication |
doi:10.18710/0JIEPQ | Video recordings of spawning behavior of Arctic charr; date: 2016-09-14; spawning ground: 3; time: morning; camera no: 2 | <|begin_of_text|><|start_header_id|>system<|end_header_id|> You are a research archivist expert in dataset metadata. Answer the question truthfully. <|eot_id|><|start_header_id|>user<|end_header_id|> Here is the Description of a dataset. Description:'This dataset contains video recordings of spawning behavior of Arctic charr (Salvelinus alpinus) in Lake Fjellfrøsvatnet (69°08′N 19°34′E), Troms, Northern Norway. The recordings were made with camera no. 2 at spawning ground 3 in the morning of 14 September 2016.A description of the data structure and format is gathered in the documentation dataset: Egeland, Torvald B.; Folstad, Ivar; Nordeide, Jarle Tryti, 2021, 'Documentation of the Spawning behavior of Arctic charr video collection', DataverseNO, https://doi.org/10.18710/VIQB0BThis dataset is part of a larger collection: Egeland, Torvald B.; Folstad, Ivar; Nordeide, Jarle Tryti, 2021, 'The Spawning behavior of Arctic charr video collection'. DataverseNO. https://doi.org/10.18710/HTM6-F146.</p' . Please return only a json list of at most 3 Keywords corresponding to the Description:.<|eot_id|><|start_header_id|>assistant<|end_header_id|> {"Answer" : ["Arctic charr","courtship","egg predation","female choice","filial cannibalism","gamete synchrony","male-male competition","mate guarding","protective behaviour","Salvelinus alpinus","sexual selection","spawning behavior","sperm competition","vibrational communication"]} <|eot_id|> | Here is the Description of a dataset. Description:'This dataset contains video recordings of spawning behavior of Arctic charr (Salvelinus alpinus) in Lake Fjellfrøsvatnet (69°08′N 19°34′E), Troms, Northern Norway. The recordings were made with camera no. 2 at spawning ground 3 in the morning of 14 September 2016.A description of the data structure and format is gathered in the documentation dataset: Egeland, Torvald B.; Folstad, Ivar; Nordeide, Jarle Tryti, 2021, 'Documentation of the Spawning behavior of Arctic charr video collection', DataverseNO, https://doi.org/10.18710/VIQB0BThis dataset is part of a larger collection: Egeland, Torvald B.; Folstad, Ivar; Nordeide, Jarle Tryti, 2021, 'The Spawning behavior of Arctic charr video collection'. DataverseNO. https://doi.org/10.18710/HTM6-F146.</p' . Please return only a json list of at most 3 Keywords corresponding to the Description:. | This dataset contains video recordings of spawning behavior of Arctic charr (Salvelinus alpinus) in Lake Fjellfrøsvatnet (69°08′N 19°34′E), Troms, Northern Norway. The recordings were made with camera no. 2 at spawning ground 3 in the morning of 14 September 2016.A description of the data structure and format is gathered in the documentation dataset: Egeland, Torvald B.; Folstad, Ivar; Nordeide, Jarle Tryti, 2021, 'Documentation of the Spawning behavior of Arctic charr video collection', DataverseNO, https://doi.org/10.18710/VIQB0BThis dataset is part of a larger collection: Egeland, Torvald B.; Folstad, Ivar; Nordeide, Jarle Tryti, 2021, 'The Spawning behavior of Arctic charr video collection'. DataverseNO. https://doi.org/10.18710/HTM6-F146.</p | Medicine, Health and Life Sciences | Arctic charr; courtship; egg predation; female choice; filial cannibalism; gamete synchrony; male-male competition; mate guarding; protective behaviour; Salvelinus alpinus; sexual selection; spawning behavior; sperm competition; vibrational communication |
doi:10.18738/T8/S0ZNEE | X-ray CT Scans of Tulipa sp. (Tulip) | <|begin_of_text|><|start_header_id|>system<|end_header_id|> You are a research archivist expert in dataset metadata. Answer the question truthfully. <|eot_id|><|start_header_id|>user<|end_header_id|> Here is the Description of a dataset. Description:'X-ray CT Scans of Tulipa_sp: Scans and voxblast image processing of a tulip (commercial source) for Wolfgang Stuppy of the Royal Botanic Gardens, Kew, UK. Scanned by Matthew Colbert on 03 April 2002. Outer petals opened during scan, so were digitally removed prior to rendering. Field of reconstruction = 30 mm; interslice spacing = 0.0627 mm. Image processing by Jessie Maisano, April 2002. Sagittal cutaway done on every two pixels, coronal cutaway done on every three pixels.Voxel Size X and Y=0.0585mm, Z=0.0627 mm. Total slices = 735.Please acknowledge The University of Texas High-Resolution X-ray CT Facility (UTCT) when using this data' . Please return only a json list of at most 3 Keywords corresponding to the Description:.<|eot_id|><|start_header_id|>assistant<|end_header_id|> {"Answer" : ["X-ray CT Scan Data Computed Tomography"]} <|eot_id|> | Here is the Description of a dataset. Description:'X-ray CT Scans of Tulipa_sp: Scans and voxblast image processing of a tulip (commercial source) for Wolfgang Stuppy of the Royal Botanic Gardens, Kew, UK. Scanned by Matthew Colbert on 03 April 2002. Outer petals opened during scan, so were digitally removed prior to rendering. Field of reconstruction = 30 mm; interslice spacing = 0.0627 mm. Image processing by Jessie Maisano, April 2002. Sagittal cutaway done on every two pixels, coronal cutaway done on every three pixels.Voxel Size X and Y=0.0585mm, Z=0.0627 mm. Total slices = 735.Please acknowledge The University of Texas High-Resolution X-ray CT Facility (UTCT) when using this data' . Please return only a json list of at most 3 Keywords corresponding to the Description:. | X-ray CT Scans of Tulipa_sp: Scans and voxblast image processing of a tulip (commercial source) for Wolfgang Stuppy of the Royal Botanic Gardens, Kew, UK. Scanned by Matthew Colbert on 03 April 2002. Outer petals opened during scan, so were digitally removed prior to rendering. Field of reconstruction = 30 mm; interslice spacing = 0.0627 mm. Image processing by Jessie Maisano, April 2002. Sagittal cutaway done on every two pixels, coronal cutaway done on every three pixels.Voxel Size X and Y=0.0585mm, Z=0.0627 mm. Total slices = 735.Please acknowledge The University of Texas High-Resolution X-ray CT Facility (UTCT) when using this data | Medicine, Health and Life Sciences | X-ray CT Scan Data Computed Tomography |
doi:10.18710/0OMOWH | Video recordings of spawning behavior of Arctic charr; date: 2016-09-21; spawning ground: 3; time: afternoon; camera no: 8 | <|begin_of_text|><|start_header_id|>system<|end_header_id|> You are a research archivist expert in dataset metadata. Answer the question truthfully. <|eot_id|><|start_header_id|>user<|end_header_id|> Here is the Description of a dataset. Description:'This dataset contains video recordings of spawning behavior of Arctic charr (Salvelinus alpinus) in Lake Fjellfrøsvatnet (69°08′N 19°34′E), Troms, Northern Norway. The recordings were made with camera no. 8 at spawning ground 3 in the afternoon of 21 September 2016.A description of the data structure and format is gathered in the documentation dataset: Egeland, Torvald B.; Folstad, Ivar; Nordeide, Jarle Tryti, 2021, 'Documentation of the Spawning behavior of Arctic charr video collection', DataverseNO, https://doi.org/10.18710/VIQB0BThis dataset is part of a larger collection: Egeland, Torvald B.; Folstad, Ivar; Nordeide, Jarle Tryti, 2021, 'The Spawning behavior of Arctic charr video collection'. DataverseNO. https://doi.org/10.18710/HTM6-F146.</p' . Please return only a json list of at most 3 Keywords corresponding to the Description:.<|eot_id|><|start_header_id|>assistant<|end_header_id|> {"Answer" : ["Arctic charr","courtship","egg predation","female choice","filial cannibalism","gamete synchrony","male-male competition","mate guarding","protective behaviour","Salvelinus alpinus","sexual selection","spawning behavior","sperm competition","vibrational communication"]} <|eot_id|> | Here is the Description of a dataset. Description:'This dataset contains video recordings of spawning behavior of Arctic charr (Salvelinus alpinus) in Lake Fjellfrøsvatnet (69°08′N 19°34′E), Troms, Northern Norway. The recordings were made with camera no. 8 at spawning ground 3 in the afternoon of 21 September 2016.A description of the data structure and format is gathered in the documentation dataset: Egeland, Torvald B.; Folstad, Ivar; Nordeide, Jarle Tryti, 2021, 'Documentation of the Spawning behavior of Arctic charr video collection', DataverseNO, https://doi.org/10.18710/VIQB0BThis dataset is part of a larger collection: Egeland, Torvald B.; Folstad, Ivar; Nordeide, Jarle Tryti, 2021, 'The Spawning behavior of Arctic charr video collection'. DataverseNO. https://doi.org/10.18710/HTM6-F146.</p' . Please return only a json list of at most 3 Keywords corresponding to the Description:. | This dataset contains video recordings of spawning behavior of Arctic charr (Salvelinus alpinus) in Lake Fjellfrøsvatnet (69°08′N 19°34′E), Troms, Northern Norway. The recordings were made with camera no. 8 at spawning ground 3 in the afternoon of 21 September 2016.A description of the data structure and format is gathered in the documentation dataset: Egeland, Torvald B.; Folstad, Ivar; Nordeide, Jarle Tryti, 2021, 'Documentation of the Spawning behavior of Arctic charr video collection', DataverseNO, https://doi.org/10.18710/VIQB0BThis dataset is part of a larger collection: Egeland, Torvald B.; Folstad, Ivar; Nordeide, Jarle Tryti, 2021, 'The Spawning behavior of Arctic charr video collection'. DataverseNO. https://doi.org/10.18710/HTM6-F146.</p | Medicine, Health and Life Sciences | Arctic charr; courtship; egg predation; female choice; filial cannibalism; gamete synchrony; male-male competition; mate guarding; protective behaviour; Salvelinus alpinus; sexual selection; spawning behavior; sperm competition; vibrational communication |
doi:10.18710/0VUUNO | Kittiwake fledging success, Hornøya 1980-2013 | <|begin_of_text|><|start_header_id|>system<|end_header_id|> You are a research archivist expert in dataset metadata. Answer the question truthfully. <|eot_id|><|start_header_id|>user<|end_header_id|> Here is the Description of a dataset. Description:'Counts of large black-legged kittiwake chicks in occupied nests towards the end of the breeding season, Hornøya 1980-201' . Please return only a json list of at most 3 Keywords corresponding to the Description:.<|eot_id|><|start_header_id|>assistant<|end_header_id|> {"Answer" : ["Breeding success","Fledging success","Kittiwake","Rissa tridactyla"]} <|eot_id|> | Here is the Description of a dataset. Description:'Counts of large black-legged kittiwake chicks in occupied nests towards the end of the breeding season, Hornøya 1980-201' . Please return only a json list of at most 3 Keywords corresponding to the Description:. | Counts of large black-legged kittiwake chicks in occupied nests towards the end of the breeding season, Hornøya 1980-201 | Earth and Environmental Sciences | Breeding success; Fledging success; Kittiwake; Rissa tridactyla |
doi:10.18710/0VUUNO | Kittiwake fledging success, Hornøya 1980-2013 | <|begin_of_text|><|start_header_id|>system<|end_header_id|> You are a research archivist expert in dataset metadata. Answer the question truthfully. <|eot_id|><|start_header_id|>user<|end_header_id|> Here is the Description of a dataset. Description:'Counts of large black-legged kittiwake chicks in occupied nests towards the end of the breeding season, Hornøya 1980-201' . Please return only a json list of at most 3 Keywords corresponding to the Description:.<|eot_id|><|start_header_id|>assistant<|end_header_id|> {"Answer" : ["Breeding success","Fledging success","Kittiwake","Rissa tridactyla"]} <|eot_id|> | Here is the Description of a dataset. Description:'Counts of large black-legged kittiwake chicks in occupied nests towards the end of the breeding season, Hornøya 1980-201' . Please return only a json list of at most 3 Keywords corresponding to the Description:. | Counts of large black-legged kittiwake chicks in occupied nests towards the end of the breeding season, Hornøya 1980-201 | Medicine, Health and Life Sciences | Breeding success; Fledging success; Kittiwake; Rissa tridactyla |
doi:10.18710/0XFSVW | Video recordings of spawning behavior of Arctic charr; date: 2016-09-16; spawning ground: 3; time: morning; camera no: 1 | <|begin_of_text|><|start_header_id|>system<|end_header_id|> You are a research archivist expert in dataset metadata. Answer the question truthfully. <|eot_id|><|start_header_id|>user<|end_header_id|> Here is the Description of a dataset. Description:'This dataset contains video recordings of spawning behavior of Arctic charr (Salvelinus alpinus) in Lake Fjellfrøsvatnet (69°08′N 19°34′E), Troms, Northern Norway. The recordings were made with camera no. 1 at spawning ground 3 in the morning of 16 September 2016.A description of the data structure and format is gathered in the documentation dataset: Egeland, Torvald B.; Folstad, Ivar; Nordeide, Jarle Tryti, 2021, 'Documentation of the Spawning behavior of Arctic charr video collection', DataverseNO, https://doi.org/10.18710/VIQB0BThis dataset is part of a larger collection: Egeland, Torvald B.; Folstad, Ivar; Nordeide, Jarle Tryti, 2021, 'The Spawning behavior of Arctic charr video collection'. DataverseNO. https://doi.org/10.18710/HTM6-F146.</p' . Please return only a json list of at most 3 Keywords corresponding to the Description:.<|eot_id|><|start_header_id|>assistant<|end_header_id|> {"Answer" : ["Arctic charr","courtship","egg predation","female choice","filial cannibalism","gamete synchrony","male-male competition","mate guarding","protective behaviour","Salvelinus alpinus","sexual selection","spawning behavior","sperm competition","vibrational communication"]} <|eot_id|> | Here is the Description of a dataset. Description:'This dataset contains video recordings of spawning behavior of Arctic charr (Salvelinus alpinus) in Lake Fjellfrøsvatnet (69°08′N 19°34′E), Troms, Northern Norway. The recordings were made with camera no. 1 at spawning ground 3 in the morning of 16 September 2016.A description of the data structure and format is gathered in the documentation dataset: Egeland, Torvald B.; Folstad, Ivar; Nordeide, Jarle Tryti, 2021, 'Documentation of the Spawning behavior of Arctic charr video collection', DataverseNO, https://doi.org/10.18710/VIQB0BThis dataset is part of a larger collection: Egeland, Torvald B.; Folstad, Ivar; Nordeide, Jarle Tryti, 2021, 'The Spawning behavior of Arctic charr video collection'. DataverseNO. https://doi.org/10.18710/HTM6-F146.</p' . Please return only a json list of at most 3 Keywords corresponding to the Description:. | This dataset contains video recordings of spawning behavior of Arctic charr (Salvelinus alpinus) in Lake Fjellfrøsvatnet (69°08′N 19°34′E), Troms, Northern Norway. The recordings were made with camera no. 1 at spawning ground 3 in the morning of 16 September 2016.A description of the data structure and format is gathered in the documentation dataset: Egeland, Torvald B.; Folstad, Ivar; Nordeide, Jarle Tryti, 2021, 'Documentation of the Spawning behavior of Arctic charr video collection', DataverseNO, https://doi.org/10.18710/VIQB0BThis dataset is part of a larger collection: Egeland, Torvald B.; Folstad, Ivar; Nordeide, Jarle Tryti, 2021, 'The Spawning behavior of Arctic charr video collection'. DataverseNO. https://doi.org/10.18710/HTM6-F146.</p | Medicine, Health and Life Sciences | Arctic charr; courtship; egg predation; female choice; filial cannibalism; gamete synchrony; male-male competition; mate guarding; protective behaviour; Salvelinus alpinus; sexual selection; spawning behavior; sperm competition; vibrational communication |
doi:10.18710/11LLTW | Fluorescence microscopy videos of mitochondria in H9c2 cardiomyoblasts | <|begin_of_text|><|start_header_id|>system<|end_header_id|> You are a research archivist expert in dataset metadata. Answer the question truthfully. <|eot_id|><|start_header_id|>user<|end_header_id|> Here is the Description of a dataset. Description:'Series of three-dimensional fluorescence microscopy videos of the rat cardiomyoblast cell-line H9c2. Where indicated in the file name, the cells were adapted to galactose (galac). Normal growth conditions are with glucose (gluc).The outer mitochondrial membranes are labelled with the double tag mCherry-EGFP-OMP-25TM (dTag), i.e., both a red and green fluorescent protein variant. dTag can be used as a sensor for acidity (or lysosomal degradation), as the green fluorescence is lost sooner in an acidic environment than the red fluorescence. Where indicated, the samples are additionally labelled with LysoTracker Deep Red (LTDR). This data is a collection of fluorescence microscopy videos acquired to study the dynamics of mitochondria and the degradation of mitochondria in lysosomes. Correlative transmission microscopy images (tra' . Please return only a json list of at most 3 Keywords corresponding to the Description:.<|eot_id|><|start_header_id|>assistant<|end_header_id|> {"Answer" : ["brightfield","correlative imaging","fluorescence microscopy","lysosomes","mitochondria","time-lapse"]} <|eot_id|> | Here is the Description of a dataset. Description:'Series of three-dimensional fluorescence microscopy videos of the rat cardiomyoblast cell-line H9c2. Where indicated in the file name, the cells were adapted to galactose (galac). Normal growth conditions are with glucose (gluc).The outer mitochondrial membranes are labelled with the double tag mCherry-EGFP-OMP-25TM (dTag), i.e., both a red and green fluorescent protein variant. dTag can be used as a sensor for acidity (or lysosomal degradation), as the green fluorescence is lost sooner in an acidic environment than the red fluorescence. Where indicated, the samples are additionally labelled with LysoTracker Deep Red (LTDR). This data is a collection of fluorescence microscopy videos acquired to study the dynamics of mitochondria and the degradation of mitochondria in lysosomes. Correlative transmission microscopy images (tra' . Please return only a json list of at most 3 Keywords corresponding to the Description:. | Series of three-dimensional fluorescence microscopy videos of the rat cardiomyoblast cell-line H9c2. Where indicated in the file name, the cells were adapted to galactose (galac). Normal growth conditions are with glucose (gluc).The outer mitochondrial membranes are labelled with the double tag mCherry-EGFP-OMP-25TM (dTag), i.e., both a red and green fluorescent protein variant. dTag can be used as a sensor for acidity (or lysosomal degradation), as the green fluorescence is lost sooner in an acidic environment than the red fluorescence. Where indicated, the samples are additionally labelled with LysoTracker Deep Red (LTDR). This data is a collection of fluorescence microscopy videos acquired to study the dynamics of mitochondria and the degradation of mitochondria in lysosomes. Correlative transmission microscopy images (tra | Medicine, Health and Life Sciences | brightfield; correlative imaging; fluorescence microscopy; lysosomes; mitochondria; time-lapse |
doi:10.18710/1OUTYI | Replication Data for: 'An introduction to network analysis for studies of medication use' edge lists | <|begin_of_text|><|start_header_id|>system<|end_header_id|> You are a research archivist expert in dataset metadata. Answer the question truthfully. <|eot_id|><|start_header_id|>user<|end_header_id|> Here is the Description of a dataset. Description:'The dataset contains the co-medicated medication pairs used in the Norwegian elderly population at January 1. 2013. The edge list consists of three variables; medication 1, medication 2, represented by ATC codes, and edges variable. The edge variable represents the number of patients who combined pairs of medications. The edge list is a preparatory form to generate a network' . Please return only a json list of at most 3 Keywords corresponding to the Description:.<|eot_id|><|start_header_id|>assistant<|end_header_id|> {"Answer" : ["Co-medication","Drug interactions","Network Analysis","Prescriptions","Registries"]} <|eot_id|> | Here is the Description of a dataset. Description:'The dataset contains the co-medicated medication pairs used in the Norwegian elderly population at January 1. 2013. The edge list consists of three variables; medication 1, medication 2, represented by ATC codes, and edges variable. The edge variable represents the number of patients who combined pairs of medications. The edge list is a preparatory form to generate a network' . Please return only a json list of at most 3 Keywords corresponding to the Description:. | The dataset contains the co-medicated medication pairs used in the Norwegian elderly population at January 1. 2013. The edge list consists of three variables; medication 1, medication 2, represented by ATC codes, and edges variable. The edge variable represents the number of patients who combined pairs of medications. The edge list is a preparatory form to generate a network | Medicine, Health and Life Sciences | Co-medication; Drug interactions; Network Analysis; Prescriptions; Registries |
doi:10.18710/1P920C | Video recordings of spawning behavior of Arctic charr; date: 2016-09-21; spawning ground: 3; time: morning; camera no: 2 | <|begin_of_text|><|start_header_id|>system<|end_header_id|> You are a research archivist expert in dataset metadata. Answer the question truthfully. <|eot_id|><|start_header_id|>user<|end_header_id|> Here is the Description of a dataset. Description:'This dataset contains video recordings of spawning behavior of Arctic charr (Salvelinus alpinus) in Lake Fjellfrøsvatnet (69°08′N 19°34′E), Troms, Northern Norway. The recordings were made with camera no. 2 at spawning ground 3 in the morning of 21 September 2016.A description of the data structure and format is gathered in the documentation dataset: Egeland, Torvald B.; Folstad, Ivar; Nordeide, Jarle Tryti, 2021, 'Documentation of the Spawning behavior of Arctic charr video collection', DataverseNO, https://doi.org/10.18710/VIQB0BThis dataset is part of a larger collection: Egeland, Torvald B.; Folstad, Ivar; Nordeide, Jarle Tryti, 2021, 'The Spawning behavior of Arctic charr video collection'. DataverseNO. https://doi.org/10.18710/HTM6-F146.</p' . Please return only a json list of at most 3 Keywords corresponding to the Description:.<|eot_id|><|start_header_id|>assistant<|end_header_id|> {"Answer" : ["Arctic charr","courtship","egg predation","female choice","filial cannibalism","gamete synchrony","male-male competition","mate guarding","protective behaviour","Salvelinus alpinus","sexual selection","spawning behavior","sperm competition","vibrational communication"]} <|eot_id|> | Here is the Description of a dataset. Description:'This dataset contains video recordings of spawning behavior of Arctic charr (Salvelinus alpinus) in Lake Fjellfrøsvatnet (69°08′N 19°34′E), Troms, Northern Norway. The recordings were made with camera no. 2 at spawning ground 3 in the morning of 21 September 2016.A description of the data structure and format is gathered in the documentation dataset: Egeland, Torvald B.; Folstad, Ivar; Nordeide, Jarle Tryti, 2021, 'Documentation of the Spawning behavior of Arctic charr video collection', DataverseNO, https://doi.org/10.18710/VIQB0BThis dataset is part of a larger collection: Egeland, Torvald B.; Folstad, Ivar; Nordeide, Jarle Tryti, 2021, 'The Spawning behavior of Arctic charr video collection'. DataverseNO. https://doi.org/10.18710/HTM6-F146.</p' . Please return only a json list of at most 3 Keywords corresponding to the Description:. | This dataset contains video recordings of spawning behavior of Arctic charr (Salvelinus alpinus) in Lake Fjellfrøsvatnet (69°08′N 19°34′E), Troms, Northern Norway. The recordings were made with camera no. 2 at spawning ground 3 in the morning of 21 September 2016.A description of the data structure and format is gathered in the documentation dataset: Egeland, Torvald B.; Folstad, Ivar; Nordeide, Jarle Tryti, 2021, 'Documentation of the Spawning behavior of Arctic charr video collection', DataverseNO, https://doi.org/10.18710/VIQB0BThis dataset is part of a larger collection: Egeland, Torvald B.; Folstad, Ivar; Nordeide, Jarle Tryti, 2021, 'The Spawning behavior of Arctic charr video collection'. DataverseNO. https://doi.org/10.18710/HTM6-F146.</p | Medicine, Health and Life Sciences | Arctic charr; courtship; egg predation; female choice; filial cannibalism; gamete synchrony; male-male competition; mate guarding; protective behaviour; Salvelinus alpinus; sexual selection; spawning behavior; sperm competition; vibrational communication |
doi:10.18710/28SRMJ | Replication data for: User expectations and willingsness to share self-collected health | <|begin_of_text|><|start_header_id|>system<|end_header_id|> You are a research archivist expert in dataset metadata. Answer the question truthfully. <|eot_id|><|start_header_id|>user<|end_header_id|> Here is the Description of a dataset. Description:'This is a questionnaire used in a project where the aim was to understand what motivates people to share self-collected health data, collected by mobile wearables and sensors' . Please return only a json list of at most 3 Keywords corresponding to the Description:.<|eot_id|><|start_header_id|>assistant<|end_header_id|> {"Answer" : ["health data sharing","health survey","mHealth","motivation","Public health","Wearable"]} <|eot_id|> | Here is the Description of a dataset. Description:'This is a questionnaire used in a project where the aim was to understand what motivates people to share self-collected health data, collected by mobile wearables and sensors' . Please return only a json list of at most 3 Keywords corresponding to the Description:. | This is a questionnaire used in a project where the aim was to understand what motivates people to share self-collected health data, collected by mobile wearables and sensors | Computer and Information Science | health data sharing; health survey; mHealth; motivation; Public health; Wearable |
doi:10.18710/28SRMJ | Replication data for: User expectations and willingsness to share self-collected health | <|begin_of_text|><|start_header_id|>system<|end_header_id|> You are a research archivist expert in dataset metadata. Answer the question truthfully. <|eot_id|><|start_header_id|>user<|end_header_id|> Here is the Description of a dataset. Description:'This is a questionnaire used in a project where the aim was to understand what motivates people to share self-collected health data, collected by mobile wearables and sensors' . Please return only a json list of at most 3 Keywords corresponding to the Description:.<|eot_id|><|start_header_id|>assistant<|end_header_id|> {"Answer" : ["health data sharing","health survey","mHealth","motivation","Public health","Wearable"]} <|eot_id|> | Here is the Description of a dataset. Description:'This is a questionnaire used in a project where the aim was to understand what motivates people to share self-collected health data, collected by mobile wearables and sensors' . Please return only a json list of at most 3 Keywords corresponding to the Description:. | This is a questionnaire used in a project where the aim was to understand what motivates people to share self-collected health data, collected by mobile wearables and sensors | Medicine, Health and Life Sciences | health data sharing; health survey; mHealth; motivation; Public health; Wearable |
doi:10.18710/2A5ROF | Video recordings of spawning behavior of Arctic charr; date: 2016-09-22; spawning ground: 3; time: evening; camera no: 3 | <|begin_of_text|><|start_header_id|>system<|end_header_id|> You are a research archivist expert in dataset metadata. Answer the question truthfully. <|eot_id|><|start_header_id|>user<|end_header_id|> Here is the Description of a dataset. Description:'This dataset contains video recordings of spawning behavior of Arctic charr (Salvelinus alpinus) in Lake Fjellfrøsvatnet (69°08′N 19°34′E), Troms, Northern Norway. The recordings were made with camera no. 3 at spawning ground 3 in the evening of 22 September 2016.A description of the data structure and format is gathered in the documentation dataset: Egeland, Torvald B.; Folstad, Ivar; Nordeide, Jarle Tryti, 2021, 'Documentation of the Spawning behavior of Arctic charr video collection', DataverseNO, https://doi.org/10.18710/VIQB0BThis dataset is part of a larger collection: Egeland, Torvald B.; Folstad, Ivar; Nordeide, Jarle Tryti, 2021, 'The Spawning behavior of Arctic charr video collection'. DataverseNO. https://doi.org/10.18710/HTM6-F146.</p' . Please return only a json list of at most 3 Keywords corresponding to the Description:.<|eot_id|><|start_header_id|>assistant<|end_header_id|> {"Answer" : ["Arctic charr","courtship","egg predation","female choice","filial cannibalism","gamete synchrony","male-male competition","mate guarding","protective behaviour","Salvelinus alpinus","sexual selection","spawning behavior","sperm competition","vibrational communication"]} <|eot_id|> | Here is the Description of a dataset. Description:'This dataset contains video recordings of spawning behavior of Arctic charr (Salvelinus alpinus) in Lake Fjellfrøsvatnet (69°08′N 19°34′E), Troms, Northern Norway. The recordings were made with camera no. 3 at spawning ground 3 in the evening of 22 September 2016.A description of the data structure and format is gathered in the documentation dataset: Egeland, Torvald B.; Folstad, Ivar; Nordeide, Jarle Tryti, 2021, 'Documentation of the Spawning behavior of Arctic charr video collection', DataverseNO, https://doi.org/10.18710/VIQB0BThis dataset is part of a larger collection: Egeland, Torvald B.; Folstad, Ivar; Nordeide, Jarle Tryti, 2021, 'The Spawning behavior of Arctic charr video collection'. DataverseNO. https://doi.org/10.18710/HTM6-F146.</p' . Please return only a json list of at most 3 Keywords corresponding to the Description:. | This dataset contains video recordings of spawning behavior of Arctic charr (Salvelinus alpinus) in Lake Fjellfrøsvatnet (69°08′N 19°34′E), Troms, Northern Norway. The recordings were made with camera no. 3 at spawning ground 3 in the evening of 22 September 2016.A description of the data structure and format is gathered in the documentation dataset: Egeland, Torvald B.; Folstad, Ivar; Nordeide, Jarle Tryti, 2021, 'Documentation of the Spawning behavior of Arctic charr video collection', DataverseNO, https://doi.org/10.18710/VIQB0BThis dataset is part of a larger collection: Egeland, Torvald B.; Folstad, Ivar; Nordeide, Jarle Tryti, 2021, 'The Spawning behavior of Arctic charr video collection'. DataverseNO. https://doi.org/10.18710/HTM6-F146.</p | Medicine, Health and Life Sciences | Arctic charr; courtship; egg predation; female choice; filial cannibalism; gamete synchrony; male-male competition; mate guarding; protective behaviour; Salvelinus alpinus; sexual selection; spawning behavior; sperm competition; vibrational communication |
doi:10.18710/2BQTJP | Replication Data for: 'epialleleR: an R/BioC package for quantifying and analysing low-frequency DNA methylation' | <|begin_of_text|><|start_header_id|>system<|end_header_id|> You are a research archivist expert in dataset metadata. Answer the question truthfully. <|eot_id|><|start_header_id|>user<|end_header_id|> Here is the Description of a dataset. Description:'AbstractConstitutional epigenetic silencing of tumour suppressor genes has been detected in a small number of cancer patients. Recent finding have indicated that low-level mosaic methylation of the BRCA1 gene promoter occurs in 5-10% of healthy individuals and is associated with a significantly elevated risk of breast and ovarian cancer. This further suggests that similar mosaic constitutional methylation may occur in other tumour suppressor genes as well, potentially being a significant contributor to cancer burden. However, detection of low-level mosaic epigenetic events requires highly sensitive and robust methodology for methylation analysis.We here present epialleleR, a computational framework for sensitive detection, quantification and visualisation of low-frequency, mosaic epimutation' . Please return only a json list of at most 3 Keywords corresponding to the Description:.<|eot_id|><|start_header_id|>assistant<|end_header_id|> {"Answer" : ["Computational Biology","DNA methylation","epialleleR","Epigenomics"]} <|eot_id|> | Here is the Description of a dataset. Description:'AbstractConstitutional epigenetic silencing of tumour suppressor genes has been detected in a small number of cancer patients. Recent finding have indicated that low-level mosaic methylation of the BRCA1 gene promoter occurs in 5-10% of healthy individuals and is associated with a significantly elevated risk of breast and ovarian cancer. This further suggests that similar mosaic constitutional methylation may occur in other tumour suppressor genes as well, potentially being a significant contributor to cancer burden. However, detection of low-level mosaic epigenetic events requires highly sensitive and robust methodology for methylation analysis.We here present epialleleR, a computational framework for sensitive detection, quantification and visualisation of low-frequency, mosaic epimutation' . Please return only a json list of at most 3 Keywords corresponding to the Description:. | AbstractConstitutional epigenetic silencing of tumour suppressor genes has been detected in a small number of cancer patients. Recent finding have indicated that low-level mosaic methylation of the BRCA1 gene promoter occurs in 5-10% of healthy individuals and is associated with a significantly elevated risk of breast and ovarian cancer. This further suggests that similar mosaic constitutional methylation may occur in other tumour suppressor genes as well, potentially being a significant contributor to cancer burden. However, detection of low-level mosaic epigenetic events requires highly sensitive and robust methodology for methylation analysis.We here present epialleleR, a computational framework for sensitive detection, quantification and visualisation of low-frequency, mosaic epimutation | Computer and Information Science | Computational Biology; DNA methylation; epialleleR; Epigenomics |
doi:10.18710/2BQTJP | Replication Data for: 'epialleleR: an R/BioC package for quantifying and analysing low-frequency DNA methylation' | <|begin_of_text|><|start_header_id|>system<|end_header_id|> You are a research archivist expert in dataset metadata. Answer the question truthfully. <|eot_id|><|start_header_id|>user<|end_header_id|> Here is the Description of a dataset. Description:'AbstractConstitutional epigenetic silencing of tumour suppressor genes has been detected in a small number of cancer patients. Recent finding have indicated that low-level mosaic methylation of the BRCA1 gene promoter occurs in 5-10% of healthy individuals and is associated with a significantly elevated risk of breast and ovarian cancer. This further suggests that similar mosaic constitutional methylation may occur in other tumour suppressor genes as well, potentially being a significant contributor to cancer burden. However, detection of low-level mosaic epigenetic events requires highly sensitive and robust methodology for methylation analysis.We here present epialleleR, a computational framework for sensitive detection, quantification and visualisation of low-frequency, mosaic epimutation' . Please return only a json list of at most 3 Keywords corresponding to the Description:.<|eot_id|><|start_header_id|>assistant<|end_header_id|> {"Answer" : ["Computational Biology","DNA methylation","epialleleR","Epigenomics"]} <|eot_id|> | Here is the Description of a dataset. Description:'AbstractConstitutional epigenetic silencing of tumour suppressor genes has been detected in a small number of cancer patients. Recent finding have indicated that low-level mosaic methylation of the BRCA1 gene promoter occurs in 5-10% of healthy individuals and is associated with a significantly elevated risk of breast and ovarian cancer. This further suggests that similar mosaic constitutional methylation may occur in other tumour suppressor genes as well, potentially being a significant contributor to cancer burden. However, detection of low-level mosaic epigenetic events requires highly sensitive and robust methodology for methylation analysis.We here present epialleleR, a computational framework for sensitive detection, quantification and visualisation of low-frequency, mosaic epimutation' . Please return only a json list of at most 3 Keywords corresponding to the Description:. | AbstractConstitutional epigenetic silencing of tumour suppressor genes has been detected in a small number of cancer patients. Recent finding have indicated that low-level mosaic methylation of the BRCA1 gene promoter occurs in 5-10% of healthy individuals and is associated with a significantly elevated risk of breast and ovarian cancer. This further suggests that similar mosaic constitutional methylation may occur in other tumour suppressor genes as well, potentially being a significant contributor to cancer burden. However, detection of low-level mosaic epigenetic events requires highly sensitive and robust methodology for methylation analysis.We here present epialleleR, a computational framework for sensitive detection, quantification and visualisation of low-frequency, mosaic epimutation | Medicine, Health and Life Sciences | Computational Biology; DNA methylation; epialleleR; Epigenomics |
doi:10.18710/2BQTJP | Replication Data for: 'epialleleR: an R/BioC package for quantifying and analysing low-frequency DNA methylation' | <|begin_of_text|><|start_header_id|>system<|end_header_id|> You are a research archivist expert in dataset metadata. Answer the question truthfully. <|eot_id|><|start_header_id|>user<|end_header_id|> Here is the Description of a dataset. Description:'This data set contains necessary data sets (simulated next-generation sequencing data, preprocessed public next-generation sequencing data, precomputed analysis results) used to evaluate performance of epialleleR (https://github.com/BBCG/epialleleR, http://www.bioconductor.org/packages/epialleleR/) - a computational framework for sensitive detection, quantification and visualisation of low-frequency, mosaic epimutations in methylation sequencing data. All the supplementary R scripts that were used for preparation, testing and analysis of data sets are also provided. For additional information please check epialleleR package README.md file, vignettes or reference citation.Please use TREE VIEW' . Please return only a json list of at most 3 Keywords corresponding to the Description:.<|eot_id|><|start_header_id|>assistant<|end_header_id|> {"Answer" : ["Computational Biology","DNA methylation","epialleleR","Epigenomics"]} <|eot_id|> | Here is the Description of a dataset. Description:'This data set contains necessary data sets (simulated next-generation sequencing data, preprocessed public next-generation sequencing data, precomputed analysis results) used to evaluate performance of epialleleR (https://github.com/BBCG/epialleleR, http://www.bioconductor.org/packages/epialleleR/) - a computational framework for sensitive detection, quantification and visualisation of low-frequency, mosaic epimutations in methylation sequencing data. All the supplementary R scripts that were used for preparation, testing and analysis of data sets are also provided. For additional information please check epialleleR package README.md file, vignettes or reference citation.Please use TREE VIEW' . Please return only a json list of at most 3 Keywords corresponding to the Description:. | This data set contains necessary data sets (simulated next-generation sequencing data, preprocessed public next-generation sequencing data, precomputed analysis results) used to evaluate performance of epialleleR (https://github.com/BBCG/epialleleR, http://www.bioconductor.org/packages/epialleleR/) - a computational framework for sensitive detection, quantification and visualisation of low-frequency, mosaic epimutations in methylation sequencing data. All the supplementary R scripts that were used for preparation, testing and analysis of data sets are also provided. For additional information please check epialleleR package README.md file, vignettes or reference citation.Please use TREE VIEW | Computer and Information Science | Computational Biology; DNA methylation; epialleleR; Epigenomics |
doi:10.18710/2BQTJP | Replication Data for: 'epialleleR: an R/BioC package for quantifying and analysing low-frequency DNA methylation' | <|begin_of_text|><|start_header_id|>system<|end_header_id|> You are a research archivist expert in dataset metadata. Answer the question truthfully. <|eot_id|><|start_header_id|>user<|end_header_id|> Here is the Description of a dataset. Description:'This data set contains necessary data sets (simulated next-generation sequencing data, preprocessed public next-generation sequencing data, precomputed analysis results) used to evaluate performance of epialleleR (https://github.com/BBCG/epialleleR, http://www.bioconductor.org/packages/epialleleR/) - a computational framework for sensitive detection, quantification and visualisation of low-frequency, mosaic epimutations in methylation sequencing data. All the supplementary R scripts that were used for preparation, testing and analysis of data sets are also provided. For additional information please check epialleleR package README.md file, vignettes or reference citation.Please use TREE VIEW' . Please return only a json list of at most 3 Keywords corresponding to the Description:.<|eot_id|><|start_header_id|>assistant<|end_header_id|> {"Answer" : ["Computational Biology","DNA methylation","epialleleR","Epigenomics"]} <|eot_id|> | Here is the Description of a dataset. Description:'This data set contains necessary data sets (simulated next-generation sequencing data, preprocessed public next-generation sequencing data, precomputed analysis results) used to evaluate performance of epialleleR (https://github.com/BBCG/epialleleR, http://www.bioconductor.org/packages/epialleleR/) - a computational framework for sensitive detection, quantification and visualisation of low-frequency, mosaic epimutations in methylation sequencing data. All the supplementary R scripts that were used for preparation, testing and analysis of data sets are also provided. For additional information please check epialleleR package README.md file, vignettes or reference citation.Please use TREE VIEW' . Please return only a json list of at most 3 Keywords corresponding to the Description:. | This data set contains necessary data sets (simulated next-generation sequencing data, preprocessed public next-generation sequencing data, precomputed analysis results) used to evaluate performance of epialleleR (https://github.com/BBCG/epialleleR, http://www.bioconductor.org/packages/epialleleR/) - a computational framework for sensitive detection, quantification and visualisation of low-frequency, mosaic epimutations in methylation sequencing data. All the supplementary R scripts that were used for preparation, testing and analysis of data sets are also provided. For additional information please check epialleleR package README.md file, vignettes or reference citation.Please use TREE VIEW | Medicine, Health and Life Sciences | Computational Biology; DNA methylation; epialleleR; Epigenomics |
doi:10.18710/2JTIOT | Replication Data for: Motion robust radiomic features in 18F-FDG PET/MRI imaging of lung cancer | <|begin_of_text|><|start_header_id|>system<|end_header_id|> You are a research archivist expert in dataset metadata. Answer the question truthfully. <|eot_id|><|start_header_id|>user<|end_header_id|> Here is the Description of a dataset. Description:'These data contain 834 extracted radiomic features from 17 non-small-cell lung cancer patients, each undergoing a 20-minute 18F-fluorodeoxyglucose positron emission tomography (PET)/magnetic resonance imaging (MRI) acquisition. Features from three PET image reconstructions were extracted: 1) free-breathing PET (PET_100%), 2) end-expiration PET (PET_40%) and 3) MRI-based motion corrected PET (PET_MoCo)' . Please return only a json list of at most 3 Keywords corresponding to the Description:.<|eot_id|><|start_header_id|>assistant<|end_header_id|> {"Answer" : ["features","gating","lung cancer","motion correction","PET","positron emission tomography","radiomics"]} <|eot_id|> | Here is the Description of a dataset. Description:'These data contain 834 extracted radiomic features from 17 non-small-cell lung cancer patients, each undergoing a 20-minute 18F-fluorodeoxyglucose positron emission tomography (PET)/magnetic resonance imaging (MRI) acquisition. Features from three PET image reconstructions were extracted: 1) free-breathing PET (PET_100%), 2) end-expiration PET (PET_40%) and 3) MRI-based motion corrected PET (PET_MoCo)' . Please return only a json list of at most 3 Keywords corresponding to the Description:. | These data contain 834 extracted radiomic features from 17 non-small-cell lung cancer patients, each undergoing a 20-minute 18F-fluorodeoxyglucose positron emission tomography (PET)/magnetic resonance imaging (MRI) acquisition. Features from three PET image reconstructions were extracted: 1) free-breathing PET (PET_100%), 2) end-expiration PET (PET_40%) and 3) MRI-based motion corrected PET (PET_MoCo) | Mathematical Sciences | features; gating; lung cancer; motion correction; PET; positron emission tomography; radiomics |
doi:10.18710/2JTIOT | Replication Data for: Motion robust radiomic features in 18F-FDG PET/MRI imaging of lung cancer | <|begin_of_text|><|start_header_id|>system<|end_header_id|> You are a research archivist expert in dataset metadata. Answer the question truthfully. <|eot_id|><|start_header_id|>user<|end_header_id|> Here is the Description of a dataset. Description:'These data contain 834 extracted radiomic features from 17 non-small-cell lung cancer patients, each undergoing a 20-minute 18F-fluorodeoxyglucose positron emission tomography (PET)/magnetic resonance imaging (MRI) acquisition. Features from three PET image reconstructions were extracted: 1) free-breathing PET (PET_100%), 2) end-expiration PET (PET_40%) and 3) MRI-based motion corrected PET (PET_MoCo)' . Please return only a json list of at most 3 Keywords corresponding to the Description:.<|eot_id|><|start_header_id|>assistant<|end_header_id|> {"Answer" : ["features","gating","lung cancer","motion correction","PET","positron emission tomography","radiomics"]} <|eot_id|> | Here is the Description of a dataset. Description:'These data contain 834 extracted radiomic features from 17 non-small-cell lung cancer patients, each undergoing a 20-minute 18F-fluorodeoxyglucose positron emission tomography (PET)/magnetic resonance imaging (MRI) acquisition. Features from three PET image reconstructions were extracted: 1) free-breathing PET (PET_100%), 2) end-expiration PET (PET_40%) and 3) MRI-based motion corrected PET (PET_MoCo)' . Please return only a json list of at most 3 Keywords corresponding to the Description:. | These data contain 834 extracted radiomic features from 17 non-small-cell lung cancer patients, each undergoing a 20-minute 18F-fluorodeoxyglucose positron emission tomography (PET)/magnetic resonance imaging (MRI) acquisition. Features from three PET image reconstructions were extracted: 1) free-breathing PET (PET_100%), 2) end-expiration PET (PET_40%) and 3) MRI-based motion corrected PET (PET_MoCo) | Medicine, Health and Life Sciences | features; gating; lung cancer; motion correction; PET; positron emission tomography; radiomics |
doi:10.18710/2JTIOT | Replication Data for: Motion robust radiomic features in 18F-FDG PET/MRI imaging of lung cancer | <|begin_of_text|><|start_header_id|>system<|end_header_id|> You are a research archivist expert in dataset metadata. Answer the question truthfully. <|eot_id|><|start_header_id|>user<|end_header_id|> Here is the Description of a dataset. Description:'These data contain 834 extracted radiomic features from 17 non-small-cell lung cancer patients, each undergoing a 20-minute 18F-fluorodeoxyglucose positron emission tomography (PET)/magnetic resonance imaging (MRI) acquisition. Features from three PET image reconstructions were extracted: 1) free-breathing PET (PET_100%), 2) end-expiration PET (PET_40%) and 3) MRI-based motion corrected PET (PET_MoCo)' . Please return only a json list of at most 3 Keywords corresponding to the Description:.<|eot_id|><|start_header_id|>assistant<|end_header_id|> {"Answer" : ["features","gating","lung cancer","motion correction","PET","positron emission tomography","radiomics"]} <|eot_id|> | Here is the Description of a dataset. Description:'These data contain 834 extracted radiomic features from 17 non-small-cell lung cancer patients, each undergoing a 20-minute 18F-fluorodeoxyglucose positron emission tomography (PET)/magnetic resonance imaging (MRI) acquisition. Features from three PET image reconstructions were extracted: 1) free-breathing PET (PET_100%), 2) end-expiration PET (PET_40%) and 3) MRI-based motion corrected PET (PET_MoCo)' . Please return only a json list of at most 3 Keywords corresponding to the Description:. | These data contain 834 extracted radiomic features from 17 non-small-cell lung cancer patients, each undergoing a 20-minute 18F-fluorodeoxyglucose positron emission tomography (PET)/magnetic resonance imaging (MRI) acquisition. Features from three PET image reconstructions were extracted: 1) free-breathing PET (PET_100%), 2) end-expiration PET (PET_40%) and 3) MRI-based motion corrected PET (PET_MoCo) | Physics | features; gating; lung cancer; motion correction; PET; positron emission tomography; radiomics |
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