Input: Claim: Urban agriculture alone can fully meet the food demands of major cities. [SEP] Text: , 2011, 2018; Drescher, 1996; Ferreira et al. , 2018; Hampwaye, 2013; Riley et al. , 2018). Its contribution to urban employment and incomes has also been hotly contested, largely because of the non-availability of reliable data on the activity, which takes place behind high security walls (in the case of urban home gardens in many Zimbabwean urban centres) and well beyond the watchful gaze of officials. The benefits of UA have been highlighted in the literature and they include the improvement of environmental quality (through green spaces), improvement of household food security, and the production of cost-effective food supplies in urban spaces (Modibedi et al. , 2021; Simatele & Binns, 2008; Simatele et al. , 2012). Several scholars have also acknowledged the importance of UA in Africa and its ubiquity in post-independence African cities. For example, Thabo Modibedi, Mosima Masekoameng, and (2021) have argued that urban community gardens have contributed to the mitigation of food insecurity in low-income urban areas in the Gauteng Province, South Africa’s commercial and industrial hub. However, studies done by the Network (AFSUN) across 11 cities in reveal that the alleged contribution of UA to the nutritional status of urban households is exaggerated, if one considers the low levels of participation in many low-income areas (Crush et al. , 2018). Similarly, studies by (2016), Bruce Frayne, Cameron McCordic, and (2014), and (2015) support the view that the contribution of UA in to the nutritional status of urban households is exaggerated. This 1. 3 billion by 2050 and a significant portion of this population will be residing in secondary cities with less than 500,000 residents. Many of these secondary cities are experiencing rapid growth that is attributable to rural–urban migration. These secondary cities experienced considerable disruptions to their local food systems following various government-enforced economic lockdowns implemented in 2020 and 2021 to slow the spread of the COVID-19 virus (FAO, 2020). The disruption to food systems by COVID-19 highlights the need to reconnect local production and consumption. One way to achieve this might be through deliberate promotion of commercial agricultural activities in the peri-urban zones of these cities so as to make them better positioned to withstand future shocks.

Output: contrast


Input: Claim: Certain claims suggest that advanced algorithms might predict emotions based on brain scans. [SEP] Text: This study explores how the potential application of responsible AI affects claims processing accuracy and identifies the most useful model for forecasting a customer’s insurance claim process. Various methods have been explored to address concerns about AI algorithm interpretability [4]. Recent studies have created metrics for the relevance of specific covariates based on their contribution to model prediction accuracy [4]. Furthermore, it investigates the variables that can be investigated to forecast insurance claims with greater precision and address any potential ethical issues by using predictive models for processing insurance claims. To prevent prejudice and ensure that clients receive the coverage they require, it is crucial to ensure that AI systems used in insurance are developed and implemented transparently, equitably, and ethically. The use of AI in the insurance sector has raised moral questions regarding transparency, fairness, and bias, particularly in the prediction of insurance claims. Consequently, there is an increasing focus on employing responsible AI within this sector. Ensuring the responsible development and implementation of AI systems involves transparent and ethical consideration of their potential impacts on individuals and society. This policy must be followed to protect consumers from unfair treatment and prevent discrimination against specific categories of individuals. In the insurance sector, predicting insurance claims is essential because it aids insurers in calculating the likelihood of an event occurring and the potential cost. The use of AI in this process has prompted questions about bias and discrimination, particularly against specific demographic groups. Responsible AI principles can direct the creation and use of prediction models to allay all worries. The data used to train the model must also be varied and representative of the community. A crucial area of concentration for the insurance business is the use of responsible AI in the forecasting of insurance claims in the USA. Moreover, the use of responsible AI for forecasting insurance claims can add to the body of knowledge regarding AI ethics and governance. AI technologies must be used responsibly, ethically, and within legal and regulatory frameworks as they become more common and significant. This study seeks to answer the following questions:(1)What model can be used to predict an efficient insurance claim process for a customer? (2)Which variable could be analyzed to anticipate insurance claims more accurately? (3)What potential ethical considerations are associated with using such predictive models? To identify best practices and prospective areas for development, this study also analyzes the existing literature on AI and insurance claim processing.

Output: pass


Input: Claim: CRISPR technology allows precise editing of specific genes. [SEP] Text: We further speculate that the discrepancy between the genomic PCR and immunofluorescence could result from a more complete co-transfection using electroporation and a bias towards easier detection of larger PCR products (i. e. , the KI and WT fragments) using ethidium bromide integration for detection. We have now included these data in the manuscript as Figure 4—figure supplement 3 and discussed this in the context of the GluA2 KO seen with TKIT (Results). Also see the Discussion. We also added a description of this methodology to the Materials and methods section of the manuscript. 2) Recent reports suggest that AAV vector genomes can integrate at DSBs created by Cas9 (PMIDs: 33087932, 31570731), and Cas9 can often create an opportunity for unintended insertions. Although PCR of genomic DNA (shown in Figure 4—figure supplement 2) detected both WT and KI alleles, it is not clear how often insertion of other sequences (with variable length) occurs, and no data at the level of DNA sequence is provided following AAV delivery methods. The fidelity of clean donor insertion could be examined by Sanger sequencing of genomic DNA clones to more completely define the results of insertion and genomic sequence changes around cut sites. This would also help to identify potential issues that may affect non-coding sequences (which, at the locations targeted here, are likely to be important regulatory elements). We are grateful to the reviewers for raising this important point. We agree that this is a necessary consideration when coupling AAVs withCas9 methods for genome editing (which is being widely adopted in the field). In fact, we now also speculate that 5’UTR integration of fragments of AAV could explain the lower efficiency in vivo with AAVs compared to in vitro with transfections. We have updated the text in the Results section to account for this possibility and include the recommended 2. The hippocampus will then be dissected, and genomic DNA amplify using a high-fidelity polymerase and a very long extension time (to account for variable sized insertions) flanking the KI sites. The PCR products will be sent for deep sequencing (as in Hanlon et al. , 2019). This will enable us to calculate the percentage of reads that have AAV insertions.

Output: pass


Input: Claim: Urban agriculture alone can fully meet the food demands of major cities. [SEP] Text: The levels of urban planning and management vary considerably from city to city, as do the urban planning policies that aim to control UA. The limited levels of urban land use planning are generally a reflection of the underdeveloped institutional capacities to plan and enforce regulations. According to (2017), a majority of local authorities that manage small urban centres in sub-are constrained by having insufficient capacity or funding to fulfill their mandates. Also, urban planning in many secondary urban centres has largely been top-down, with limited input from stakeholders. Urban transformations in secondary cities in sub-have generated renewed interest in food systems resilience in smaller towns. Two main questions are pertinent. First, will the 7,500 secondary cities that account for 48% of Africa’s urban centres be able to achieve Goal 2 on hunger eradication by 2030? Second, is UA making a meaningful contribution to the urban food system, especially food production? While urban development in sub-is characterized by rapid population growth and increasing urban food insecurity, secondary urban centres such as Nakuru (Kenya), Ndola (Zambia), and Karoi (Zimbabwe) have recorded high growth rates over the past 20 years, and this has had consequential effects on urban food security livelihoods. Nakuru is a secondary city whose population growth during the past two decades has been in excess of job creation capacity. This has given rise to urban informality characterized by numerous street trading activities and informal settlements. Between 1969 and 2020, the population of Nakuru increased from 47,000 to 383,000. The high rate of population growth has been accompanied by rising poverty and an uptake of UA (Foeken & Owuor, 2008; Owuor, 2006). In Nakuru, UA activities in the peri-urban zone have contributed to the city’s local food system, as some of the produce finds its way to local vegetable markets (Foeken & Owuor, 2008; Owuor, 2006). However, it is unlikely that the contribution of UA to local food production can be maintained because the urban development projects that have been implemented in recent years in the peri-urban zone (Willkomm et al. , 2021) and in open spaces will reduce the space available for UA. Ndola is an intermediate city with a population of about 500,000, including a large labour force that is employed in copper mining and allied industries.

Output: contrast


Input: Claim: Certain claims suggest that advanced algorithms might predict emotions based on brain scans. [SEP] Text: In recent years, several businesses have started using AI to automate jobs that people are typically hired to complete, such as detecting fraudulent movements, choosing resumes, processing credit-related requests, and releasing those people for high-level duties [5]. According to a survey of 2,360 business executives about the use of AI, more than 62% of executives said that AI solutions increased their revenues, decreased their costs, and enhanced customer satisfaction [6]. AI has proven its value in different business sectors by quickly establishing automated environments that are controlled and digitally upgraded for maximum efficiency in 2017 [7]. The use of AI in Tanzania’s healthcare sector includes applications for disease prediction and diagnosis, vaccine stock optimization, and health supply chain management [8]. AI can assist in the methods mentioned above to improve customer satisfaction and revenues and cut down on fraud, inefficient time use, and operational complexity [9]. One of the important areas across Europe where AI can address many issues with the health system is the health sector [10]. Several problems prevent medical AI from being used properly and effectively. These confrontations include data privacy, intellectual property rights, accountability, openness, cybersecurity, accuracy, performance, bias, and discrimination. Thus, it is advised that strategic decisions should be made when putting AI-based innovations into practice for companies to make sure that i) they are responsible, ii) the challenges are properly addressed, and iii) there is a balance between opposing interests and values [10, 11]. Besides the hazards, the growing application of AI exacerbates intrinsic problems with trust and accountability. Enterprises must be aware of the difficulties and dangers associated with AI and take these into full consideration when presenting suggested plans to effectively address these issues [11]. Adaptive boosting (AdaBoost), a whitebox algorithm, outperforms all additional models in terms of performance, aids in lowering operating costs for providers, improves the speed and accuracy of the insurance claim process and allows patients to concentrate on their recovery rather than navigating the insurance claim appeals process [12]. Because of the unstable nature of intelligent applications, the theoretical paradigm for the growth of responsible AI was founded on perceived risk theory. Digital healthcare AI risks are inversely correlated with responsible AI [13]. There should be a complete framework for responsible AI that businesses can use to emphasize and address important issues when developing and implementing responsible AI applications.

Output: pass


Input: Claim: CRISPR technology allows precise editing of specific genes. [SEP] Text: An efficient and specific -Cas9 genome editing system targeting soybean phytoene desaturase genes access Published: 15 February 2022 An efficient and specific -Cas9 genome editing system targeting soybean phytoene desaturase genes Mimmie Lu1 & Lining Tian1 BMC Biotechnology 82. Transformed plants for all five constructs were recovered. Dwarf and albino phenotypes were observed in transgenic plants harboring the constructs targeting both PDS genes. Gene editing at the desired loci was detected in the majority of T0 transgenic plants, with 75–100% mutation efficiencies. Indel frequencies varied widely among plants (3–100%), with those exhibiting visible mutant phenotypes showing higher frequencies (27–100%). Deletion was the predominant mutation type, although 1-nucleotide insertion was also observed. Constructs designed to target only one PDS gene did not induce mutation in the other homologous counterpart; and no mutation at several potential off-target loci was detected, indicating high editing specificity. Modifications in both PDS genes were transmitted to T1 progenies, including plants that were negative for transgene detection. Strong mutant phenotypes were also observed in T1 plants. ConclusionsUsing simple constructs containing one guide RNA, we demonstrated efficient and specificCas9-mediated mutagenesis in stably transformed soybean plants, and showed that the mutations could be inherited in progenies, even in plants that lost transgenes through segregation. The established system can be employed to edit other genes for soybean trait improvement. BackgroundGenome editing using the clustered regularly interspaced short palindromic repeats/-associated 9 (/Cas9) system has emerged as a versatile tool to modify genes at precise locations. It was initially discovered as bacterial immune system against viruses and other foreign nucleic acids such as plasmids [1,2,3,4,5]. refers to direct repeats in bacterial genome separated by short stretches of variable sequences called spacers derived from invading genetic material [1, 4, 6]. Cas genes are often located adjacent to which encode proteins with RuvC-like and HNH-like nuclease domains [5, 7,8,9]. Transcription of locus generates a non-coding precursor RNA cleaved into short (crRNAs), which direct the Cas proteins to cleave foreign nucleic acids containing complementary target sequences [2].

Output: corroborate


Input: Claim: Urban agriculture alone can fully meet the food demands of major cities. [SEP] Text: The city experienced a long period of steady growth from the 1960s to the early 1990s. However, following the decline of copper mining and de-urbanization in the copper belt during the 1990s, the rate of growth has declined. The location of Ndola in the country’s copper mining region has resulted in the growth of close ties with the global economy and also with a huge rural hinterland that has provided the mines with cheap semi-skilled labour. Karoi, on the other hand, is a small agricultural town of fewer than 35,000 people, situated in the heartland of one of Zimbabwe’s most productive farming regions. However, with the repeal of influx control measures following the country’s attainment of majority rule in 1980, Karoi experienced relatively rapid growth during the 1980s and 1990s. This 7. 1 highlights several common elements of the UA experiences of Karoi, Nakuru, and Ndola, despite their considerable differences in terms of size, economic base, and UA policies. The table presents key aspects of UA in these urban centres, captured in the following broad themes: Theme 1 highlights the main factors that motivate households to engage in UA; Theme 2 presents the socio-demographic profiles of the urban farmers in terms of age, gender, educational attainment, and income class; Theme 3 highlights the dominant UA activities; Theme 4 identifies the bottlenecks that are blocking the uptake of UA; and Theme 5 provides an overview of the policy environments in the three urban centres and their effects on UA. Table 7. 1 Key aspects of urban agriculture in Karoi (Zimbabwe), Nakuru (Kenya), and Ndola (Zambia)Full size tableTheme 1: Drivers of UAUA is driven by a variety of factors, including urban food insecurity, urban poverty, entrepreneurial aspirations, desire for ethnic foods, and shocks to the urban food systems that are caused by economic, environmental (e. g. , drought), and health crises (e. g. , government-induced COVID-19 lockdowns). Table 7. 1 highlights the main reasons why both poor households and relatively well-resourced commercial farmers have engaged in UA in the three secondary urban centres.

Output: contrast


Input: Claim: Certain claims suggest that advanced algorithms might predict emotions based on brain scans. [SEP] Text: Governance provides an ongoing foundation for all other aspects and assists businesses in creating AI that complies with the relevant regulations and upholds ethical standards [14]. The operation of the Apriori algorithm consists of two steps: First, obtain frequent item sets of the largest possible size, and then, use these frequent item sets to generate rules by locating all their subsets [14]. Both supervised and unsupervised machine learning (ML) algorithms were used, including support vector machine (SVM), logistic regression, naive Bayes, random forest (RF) classifiers, deep neural networks, and AdaBoost. They examined the efficacy of every algorithm for detecting blockchain fraud and discovered that RF, AdaBoost, and SVM generated effective outcomes [15]. The aftereffects of the different processes reduced the number of claims filed as a text message was sent to the insured individual that full or a portion of a claim may be denied. Furthermore, it might impose conditions on the claimant as the decision is being made, which could prolong the process [16]. The paper’s primary goal is to use the Apriori algorithm to find similarities between medical bills and purchasing bills. This method searches a database of frequently occurring item sets to identify item sets whose occurrences exceed a specified threshold [17]. The main objective while building an AI solution is to identify the easiest model that performs the best. Using ML to solve problems in trading and investment management has made things more useful and opened new options for the economy. This is possible because computers are getting faster, data storage costs are going down, and big data is ready to use [18, 19]. A supervised learning rule first completes a foundational task using sample data and then attempts to build a temporary performance, leading to the plotting of new input vectors. In several application areas, supervised learning algorithms are used. A comparable goal is for the supervised learning rule to cut back superbly from the knowledge to the contained objects in the best possible setting, helping the rule to appropriately index the class labels for near occurrences [20–22]. It is necessary to continuously test various AI algorithms because the performance of an AI model varies with the core data structures. AI systems’ accuracy, simplicity, and inter-portability can all be traded off. To choose the finest-performing AI algorithm with the least amount of complexity and the greatest degree of interpretability, it is crucial to investigate several AI algorithms.

Output: pass


Input: Claim: CRISPR technology allows precise editing of specific genes. [SEP] Text: system from Streptococcus pyogenes is among the best characterized. It is consisted of nuclease Cas9, crRNA, and an auxiliary trans-activating crRNA (tracrRNA) required for processing of crRNA into functioning units [7, 10]. In the engineeredCas9 system, crRNA and tracrRNA are fused into a single guide RNA (sgRNA) [7, 11]. Cas9 is guided to specific genomic locus by sgRNA containing a 20-nucleotide (nt) target sequence, which immediately precedes the protospacer adjacent motif (PAM), with the sequence 5’-NGG-3’ in the system derived from Streptococcus pyogenes [7, 11,12,13]. At the target site, Cas9 RuvC and HNH-like nuclease domains each cleave one DNA strand, creating a double stranded break (DSB) at 3 base pairs (bp) upstream of PAM [7, 9]. The cleaved genomic locus then activates DNA damage repair, either by nonhomologous end joining (NHEJ) pathway or homology-directed repair (HDR) [11,12,13]. In the absence of a repair template, the error prone NHEJ pathway is activated, creating insertion or deletion (indel) mutations. HDR pathway requires the presence of homologous DNA template surrounding the DSB, which can be delivered by a plasmid or single-stranded DNA oligos [12, 13]. Once mutations are induced at target loci, novel traits can be retained in transgene-free mutants through transient Cas9/sgRNA expression or Mendelian gene segregation. Genome editing usingCas9 has been employed in various plant species of commercial importance such as rice [13], wheat [13, 14], apple [15], tomato [16], grape [17, 18], melon [19], etc. This technology has become a promising tool for crop trait improvement. Soybean (Glycine max L. Merr. ) is a globally important crop that provides a rich source of protein and oil. Since year 2015, genome editing in soybean has been performed by several research groups, often using hairy root system [20,21,22,23,24,25,26,27,28,29].

Output: corroborate


Input: Claim: Urban agriculture alone can fully meet the food demands of major cities. [SEP] Text: Lack of access to food, because it is either too expensive or unavailable for purchase, is one of the main reasons why many low-income households have resorted to UA under fairly challenging conditions (Foeken & Owuor, 2008; Gondo et al. , 2017; Voleníková & Opršal, 2016; Willkomm et al. , 2021). Urban food production is largely a response by the urban poor to inadequate, unreliable, and irregular access to food supplies (Foeken & Owuor, 2008; Modibedi et al. , 2021; Zezza & Tasciotti, 2010). The need to produce fresh and culturally preferable food has also compelled some middle-income households to grow the food they consume. The persistence of UA in African cities is attributed to factors such as expensive urban food, urban food deserts, high unemployment levels, and food rights initiatives. Theme 2: Profile of Urban FarmersTable 7. 1 shows that in Nakuru, Ndola, and Karoi, the major groups involved in UA are women, middle-aged residents (over 40 years old), people with regular incomes, and fairly educated urban dwellers with high school education (Foeken & Owuor, 2008; Gondo et al. , 2017; Voleníková & Opršal, 2016). The limited involvement of young people in the activity implies reduced opportunities for potential transfer of UA skills and knowledge to the younger generation. Regarding the role of women involved in UA, it is essential to think beyond the numbers and to consider women’s involvement in terms of their contribution to the gendering of UA (Hovorka & Lee-Smith, 2006; Hovorka et al. , 2009; Ishani, 2009). It is clear from all three urban centres that since women are actively engaged in UA activities they are contributing to urban food and nutrition security in ways that are often missed by urban food studies that focus on where households buy their food. However, further studies in Nakuru, Ndola, and Karoi could try to establish whether households that are engaged in UA are more food secure than households that do not participate in the activity. An earlier study by (2004) also argues for looking at UA through an alternative entrepreneurship prism.

Output: contrast


Input: Claim: Certain claims suggest that advanced algorithms might predict emotions based on brain scans. [SEP] Text: The intended study uses six AI algorithms: two interpretable, two whiteboxes, and two blackboxes [23]. Materials and methodsNecessary data were gathered to construct ML models based on USA health insurance claims by people aged 18 to 60 in four different regions [24]. The data covers information about insurance claims, including age, gender, body mass index (BMI), blood pressure, diabetic status, number of children, smoking status, and region of the insured person. It must be cleaned up and sorted before the data is used to build ML models. Data cleaning eliminates erroneous data by extracting input and output features that contribute to effectively fitting the best model. A description of the features is given in Table 1. Data preparation is the vital process of refining and adapting data to make it well-suited for ML algorithms. The quality of this process significantly influences the model’s performance. It encompasses tasks such as data cleansing, exploratory data analysis (EDA), standardization, and reducing dimensionality. Data cleaning is the key step of the following retrieval, which involves identifying and eliminating erroneous, misleading, incomplete, and corrupt data. By using a mean substitution, a dummy value that treats the missing feature values as missing values can take their place. Table 1. Description of health insurance databaseNumberVariable nameExplanation1. AgeAge of primary beneficiary2. GenderGender of the beneficiary3. of the beneficiary (kg/m2) using the ratio of height to weight, ideally 18. 5 kg/m2 to 25 kg/m24. Blood pressureWhether the insured person has blood pressure (mmHg) or not5. DiabeticWhether the insured person is diabetic or not6. ChildrenNumber of children of the insured person7. SmokerWhether the insured person is a smoker or not8. RegionThe residential areas of the beneficiary in the USA are and Northwest USA9. ClaimAmount of the insurance claimDisplay full sizeEDA is applied to understand the data before applying the ML model. Data visualization with graphs reveals concealed connections between features that cannot be detected by simply viewing the dataset. The study used a heatmap to visualize the correlation between the pair of variables and to understand the significance of all the explanatory variables concerning the response variable in Figure 1. The heatmap shows a strong relationship between blood pressure and insurance claims, followed by BMI, which has an impact on insurance claims. Display full sizeFigure 1.

Output: pass


Input: Claim: CRISPR technology allows precise editing of specific genes. [SEP] Text: To evaluate gene targeting efficiency and specificity, we created three constructs targeting each PDS gene specifically as well as two constructs targeting both genes simultaneously, using one guide RNA in each construct. Instead of using cotyledonary nodes derived from germinated seedlings, we performed Agrobacterium-mediated transformation of cv. Williams 82 using ‘half-seed’ explants dissected directly from overnight-imbibed seeds. Transformed plants for all constructs were recovered. Mutations at desired loci were induced in T0 plants with high specificity and efficiencies, and were transmitted to T1 progenies. Simultaneous targeting of both PDS genes resulted in visible mutant phenotypes in both T0 and T1 generations. Our efficient and specificCas9 genome editing system can be employed to modify other genes in soybean through whole plant transformation for agronomic trait improvement. ResultsSoybean is a palaeopolyploid organism which underwent genome duplication in ancient times, nearly 75% of its genes are in multiple copies [44]. The soybean genome contains two highly homologous PDS genes: Glyma. 11g253000 on chromosome 11 (hereafter named GmPDS11g) and Glyma. 18g003900 on chromosome 18 (hereafter named GmPDS18g). The two paralogues have 13 exons in each, sharing 96% identity in nucleotide coding sequence (Additional file 1, Figure S1), and 98% identity at amino acid level (Additional file 2, Figure S2). We created an array of genome editing constructs, including two constructs (GmPDS1 and GmPDS3) targeting GmPDS18g specifically, one construct (GmPDS7) targeting GmPDS11g specifically, and two constructs (GmPDS8 and GmPDS9) targeting both genes simultaneously at conserved regions (Table 1). We used -PLANT online tool [45] to select guide sequences targeting each gene specifically. Sequences targeting both PDS genes simultaneously were designed manually by selecting 20 nucleotides in the conserved regions immediately preceding PAM ‘-NGG-’, on exons in the upstream locations. The sequences were then used as queries for Tool (BLAST) in Phytozome [46] to check for specificity.

Output: corroborate


Input: Claim: Urban agriculture alone can fully meet the food demands of major cities. [SEP] Text: The various studies conducted in the three secondary urban centres help to dispel the myth that people engaged in UA in Africa are predominantly poor and recent arrivals from rural areas who have run out of livelihood options. A study by David Mkwambisi, Evan Fraser, and (2011) on UA in Lilongwe and Blantyre (Malawi) also found that UA is not a preserve of the poor. The study also noted that urban food production in the two cities in Malawi is dominated by high-income households because, unlike low-income households, this group of urban farmers has the capacity to cultivate larger pieces of land and to purchase the required agricultural inputs, such as seeds, fertilizers, and pesticides. They also hire farm labour from low-income urban neighbourhoods. While this creates employment for a group of people who would have been unemployed, it also tends to create a group of urban farm labourers and to reproduce social inequalities. Urban farmers are commonly portrayed through a poverty lens as resource-poor urbanites who engage in undercapitalized micro-farming activities as a livelihood strategy, but the experiences of Ndola and Nakuru suggest that while poverty is the driving force for many low-income urban farmers, many households have engaged in the activity for entrepreneurial purposes. It is also worth noting that the most poverty-stricken households do not own spaces they can use for cultivation, and neither can they afford to rent. In fact, the poor tend to be transient and do not have the cash and social capital to enable them to access urban land for cultivation. In view of this, the open spaces in Karoi, Nakuru, and Ndola should not be perceived as sites of survivalist pursuits of the poor; instead they should be viewed as spaces of resistance to top-down urban planning approaches by both resource-rich and resource-poor households. Theme 3: Dominant ActivitiesCultivation of maize and leafy vegetables is practiced by urban farmers in the three secondary urban centres, with leafy vegetables generally grown in home gardens and maize in open spaces during the rain season. Urban farmers in Nakuru and Ndola with relatively large plots are able to keep chickens, but in Karoi the municipal bylaws make it illegal to keep livestock in urban areas. Theme 4: Urban FarmersUrban farmers in the three secondary urban centres face several common challenges, such as limited access to suitable land for cultivation, land tenure insecurity, and theft of produce before harvesting.

Output: contrast


Input: Claim: Certain claims suggest that advanced algorithms might predict emotions based on brain scans. [SEP] Text: Heatmap of variable interactions in health insurance claimsDifferent graphs are also displayed in Figures 2 and 3 to observe unique values of the categorical variables and the distribution of explanatory variables respectively. The age distribution is even, with a slight increase among 20–30-year-olds. BMI is normally distributed, with a peak around 30–35. Blood pressure readings are right skewed, mostly between 80–100 mmHg (1 mmHg = 0. 13332 kPa) (Figure 3). The number of children per individual decreases as the number increases, with most having 0–2 children. Claim amounts are right-skewed, with most of the claims below $10,000, indicating a dataset that likely represents a demographic of young to middle-aged adults with a range of health-related characteristics and insurance claim amounts. Display full sizeFigure 2. Number of unique values of categorical variablesDisplay full sizeFigure 3. Frequency distribution of the numerical variables. A. Histogram of age; B. histogram of BMI; C. histogram of blood pressure; D. histogram of children; E. histogram of claimThen, one-hot encoding involves transforming categorical data into a format that can contribute to ML algorithms to increase prediction accuracy. ML commonly uses one-hot encoding to handle categorical input. This gives the idea of transforming all categorical values into numerical values. Categorical data can be more expressively represented by one-hot encoding. The need for it arises from the fact that many ML algorithms fail to operate and produce the desired results when given categorical input. Data is divided into portions for training and testing, with 80% of the data being used for training and 20% of the data for testing. The dataset contains 1,065 rows and 14 columns for training and the dataset contains 267 rows and 14 columns for testing. After the data preparation is done, the next step involves transitioning into model building. Here, the target variable has discrete values, and different regression models are used for future claim prediction. Therefore, the study used different performance measures for all models, using parametric and non-parametric regression models, such as decision tree (DT), SVM, RF regressor (RFR), extreme gradient boosting (XGBoost), k-nearest neighbors (KNN) algorithm, and linear regression (LR).

Output: pass


Input: Claim: CRISPR technology allows precise editing of specific genes. [SEP] Text: H GmPDS9 plantlet with variegated leaves (pointed by arrow)Full size imageMutations were detected in T0 GmPDS1, GmPDS3, and GmPDS7 plants, in the desired loci specificallyTo analyze gene editing, we sequenced PDS gene fragments encompassing the target sites in GmPDS1, GmPDS3, and GmPDS7 T0 plants verified for transformation. To examine the presence of basal mutation in the regions, we also sequenced regenerated wild type controls, as well as several GmPDS3 plants that were negative for transgene detection. In all cases, gene fragments amplified from wild type plants matched the reference sequences. Plants that were negative for transgene detection also showed no sequence change (Additional file 4: Table S2), indicating absence of basal mutation in the loci. Mutations at target sites were detected in all GmPDS1 and GmPDS3 transgenic plants, with 100% mutation efficiencies. Sequence changes were also detected in three GmPDS7 transformants, corresponding to 75% mutation efficiency (Table 2). Table 2 Summary ofCas9-induced mutations in T0 plantsFull size tableFor each transgenic plant, we sequenced both GmPDS11g and GmPDS18g regions. The target fragments were amplified from genomic DNA, cloned into plasmid pGateG [48], and transferred into E. coli. Plasmids were extracted from randomly selected E. coli colonies and sequenced. Of the two GmPDS1 plants, 6. 5% and 16% of sequenced clones had mutations in GmPDS18g, these numbers represent indel frequencies at the target site. Likewise, the five transgenic GmPDS3 plants had indel frequencies of 8%, 12%, 23%, 74% and 88% in GmPDS18g (Table 2, Additional file 4: Table S2). On the other hand, no sequence change was detected in the homologous counterparts in GmPDS11g, providing evidence of specific targeting. Indels in GmPDS11g were detected in three GmPDS7 transformants, among 9%, 14%, and 21% of sequenced clones (Table 2, Additional file 4: Table S2).

Output: corroborate


Input: Claim: Urban agriculture alone can fully meet the food demands of major cities. [SEP] Text: Projects’ and Frederic R. Siegel2 Part of the book series: SpringerBriefs in Geography (()) 1178 Accesses AbstractMany old and “modern” cities have been built on terrain that was previously vegetated and part of biologically diverse ecosystems. This was often on productive farmland that was not protected from encroachment as municipalities expanded and opened pristine areas to development. The encroachment continues as rural citizens and their families are attracted to urban centers for the way of life they seemed to offer. This starts with employment possibilities, education for workers children, and family health services as manufacturing/industrial operations and large and small businesses that serviced them spurs economic development. Agricultural projects are located mainly away from population centers, be they major metropolises or smaller cities. They provide food security for urban citizens through “brought into markets” in-ground crops, bush crops, and tree crops they cultivate, and through animal husbandry (e. g. , beef and dairy cattle, poultry, hogs, sheep). The last 6. 1 IntroductionMany old and “modern” cities have been built on terrain that was previously vegetated and part of biologically diverse ecosystems. This was often on productive farmland that was not protected from encroachment as municipalities expanded and opened pristine areas to development. The encroachment continues as rural citizens and their families are attracted to urban centers for the way of life they seemed to offer. This starts with employment possibilities, education for workers children, and family health services as manufacturing/industrial operations and large and small businesses that serviced them spurs economic development. Agricultural projects are located mainly away from population centers, be they major metropolises or smaller cities. They provide food security for urban citizens through “brought into markets” in-ground crops, bush crops, and tree crops they cultivate, and through animal husbandry (e. g. , beef and dairy cattle, poultry, hogs, sheep). The last 6. 2 Food Insecurity: Stemming UrbanizationMany in the global population especially babies, young children, and the aged in Africa and the suffered with chronic malnutrition and starvation from famine in 2017. This is the result of drought, people being displaced from their homes by warring factions and decisions not to allow humanitarian food supplies to reach starving populations, thus exacerbating the famine problem.

Output: contrast


Input: Claim: Certain claims suggest that advanced algorithms might predict emotions based on brain scans. [SEP] Text: Supervised learning is applied to data separated into input variables, or features, and an output or target variable. Classification and regression techniques are supervised. Supervised ML algorithms perform algorithm classification. The dataset used for the analysis does not belong to the category of binary classification. Classification algorithms are employed for categorical variables, and regression methods are employed for continuous variables. Regression algorithms can estimate claim amounts for insurance companies. The ML classification algorithms applied to the prediction analysis are and KNN. The key goal of designing an AI solution is to explore the simplest and most effective model that has better performance than the rest of the models used in the 4. Display full sizeFigure 4. ML framework for health insurance claims analysisThe target variable is discrete values, and different regression models are used for future claim prediction. Therefore, different performance measures for all models, using parametric and non-parametric regression models, such as algorithm, and LR are applied. After model selection, the training data is used to initially train the models with all available features. Subsequently, classification algorithms are applied, focusing exclusively on the features chosen through feature selection techniques. Lastly, a comprehensive comparative analysis of the models is performed to pinpoint the most effective model for the datasets. This evaluation encompasses the utilization of performance measures and feature importance for distinct algorithms to assess the best performance of the model. ResultsThe dataset consists of 1,340 rows and 11 columns, 10 of which are features, and 1 target variable of the dataset for better understanding. After the data is gathered, the next step is data preparation. First, missing values are checked, and then several statistics of the features are performed for the observation. One-hot encoding is done before splitting the training, and the testing dataset is performed for the “claim” to understand the distribution and patterns of different features in different regions, accompanied by additional features. The data shows gender distribution among insurance claimants, with males representing 50. 3% and females slightly lower at 49. 7%, suggesting an almost even split in insurance claim ratios between the two sexes. It also displays that diabetic patients account for 47. 8% of the claimants, nearly half, compared to nondiabetic patients at 52. 2%. Moreover, smokers are 20. 6% and 79. 4% of non-smokers request for the insurance claim (Table 2). Table 2. Insurance claims based on gender, diabetic patients, and smokersVariableInsurance claim (%)GenderMale50.

Output: pass


Input: Claim: CRISPR technology allows precise editing of specific genes. [SEP] Text: No mutation was detected in the GmPDS18g counterpart, again demonstrating gene targeting specificity. The observed mutations predominantly occurred in the guide RNA regions, a few bp upstream of PAM. The vast majority were short deletions of one to several nucleotides (Fig. 3). Longer deletions of over 30 nucleotides were detected in some clones. One-nt insertion in front of PAM was also common. Insertions longer than 1-nt were not detected. Fig. 3Detection of mutations in GmPDS1, GmPDS3, and GmPDS7 T0 plants. A Examples of sequencing chromatograms showing mutations. The 20-nt target sequence is highlighted in blue, PAM sequence is indicated in the green box, and mutations are circled in red. B Representative mutations at target sites. Individual T0 plant harboring the mutation is indicated to the right of each sequence. Wild type sequence is shown at the top with the 20-nt guide sequence in blue and PAM sequence in green. Mutations are shown in red. The number of mutated nucleotides is indicated to the right of each sequence. -: deletion, + : insertion. The number of clones for each mutation is indicated in bracketsFull size imageSimultaneous targeting of both PDS genes at conserved regions resulted in dwarf and albino phenotypesA total of 21 GmPDS8 T0 plantlets, of 17 independent events, were regenerated. Among those, 19 were confirmed for transformation by PCR. A range of phenotypes were observed: six plantlets were strongly dwarf and albino (Fig. 2E), typical of the pds loss of function mutant [40]; three were partially dwarf with albino or variegated leaves; three had pale leaves; one had variegated leaves, but not dwarf (Fig. 2F); and eight had phenotypes similar to wild type. Of the six shoots with strong mutant phenotypes, only three could form roots. Due to developmental defects, only two T0 plants with visible mutant phenotypes (line #3 and #5) survived in soil. Fifteen plantlets of independent events were recovered from GmPDS9 transformation. Among those, one plantlet showed variegated leaves (Fig. 2H); three shoots were completely or partially albino that did not elongate and form roots (Fig.

Output: corroborate


Input: Claim: Urban agriculture alone can fully meet the food demands of major cities. [SEP] Text: If there is agricultural land that adds to the food security and it is nearby expanding cities, this land should be preserved and neither encroached upon by growing populations nor be subject to seizure by eminent domain laws for economic development. Here we have a moral question: Should cities limit population growth from in-migration and immigration to prevent encroachment? The flow of people to cities can be arrested if urban attractions are not driving forces. This means improving the services available in rural areas by subsidizing farming, increasing employment opportunities, and upgrading and increasing educational offerings. There should also be improvement in rural health care facilities with professional and support staff, and well stocked with basic medications, and with ready access to diagnostic medical equipment. This solution is easily prescribed but difficult to bring to fruition mainly for economic reasons but also by the reluctance of some trained personnel to move to rural areas such as those needed to provide professional health services. Nonetheless, a start in bringing this prescription to reality may slow urban population influx from in-migration and lessen the possible encroachment on productive land. 6. 3NeedsAs indicated above, it is good practice to preserve farmland near an urban center not only from population encroachment but also from processes that can degrade good agricultural soil and affect the quality and yield of food crops grown and hence food security. The former action requires a municipal decree that will prevent squatting and establishment of shantytowns on protected land. The latter requires that consultants assess erosion potential of farm acreage and provide solutions to prevent erosion by wind (e. g. , change plow and seed method to slice and seed; plant vegetation wind breaks at peripheries of croplands) or by flowing water after heavy rains (e. g. , by diversion channels to safe discharge locations) if this could be a problem. When protected land is to be used for agriculture, experts have to determine what water requirements will be for crops that are planned and consider how this might change if crops are rotated (alternated) and thus affect urban water security. Will crops be irrigated or rain fed, or be sustained by a combination of both? If irrigation is necessary, will the irrigation technique to be used preserve water supplies (e. g. , drip irrigation that needs initial investment and subsequent maintenance) or will it lose precious water to evaporation during arm irrigation? Will the irrigation water come from aquifers or surface waterways?

Output: contrast


Input: Claim: Certain claims suggest that advanced algorithms might predict emotions based on brain scans. [SEP] Text: 3Female49. 7DiabeticYes47. 8No52. 2SmokerYes20. 6No79. 4Display full sizeIt is observed that insured individuals in the Southeast USA region report the highest number of insurance claims, followed by those in the and Northeast USA (Table 3). Table 3. Insurance claims based on regionRegionInsurance claim (%)Southeast USA33. 2Northeast USA17. 3Southwest USA23. 6Northwest USA25. 9Display full sizeIt is also observed that average insurance claims are around $13,325, and most of the insurance claims range between $1,200 and $14,000. Apart from these observations, the Northeast USA is less likely to file insurance claims than other regions (Tables 3 and 4). Table 4. Statistics on attributes in the health insurance databaseStatisticsAge (years)BMIBlood pressure (mmHg)ChildrenClaim ($)Minimum1816. 008001,121. 87Maximum6053. 10140563,770. 43Mean38. 0930. 6694113,325. 25Standard deviation11. 116. 1211112,109. 62Display full sizeThe insurance claims data shows an inverse relationship between the number of children and the likelihood of filing a claim in the USA (Figure 5). It also indicates that claimants within the age group of 50 to 60 years are exclusively female, while those under 25 are exclusively male. Display full sizeFigure 5. Numeric based on gender data. A. Histogram of age; B. histogram of BMI; C. histogram of blood pressure; D. histogram of children; E. histogram of claimThe regional gender distribution of claims across the USA, with the Southeast USA leading at 33. 2%, followed by the Northwest USA at 25. 9%, the Southwest USA at 23. 6%, and the Northeast USA at 17. 3% (Table 3 and Figure 6). Display full sizeFigure 6. Numeric based on four regions. A. Histogram of age; B. histogram of BMI; C. histogram of blood pressure; D. histogram of children; E. histogram of claimMoving to smoking habits, 20. 6% of claims are from smokers, whereas a significantly larger portion, 79. 4%, comes from non-smokers (Figure 7).

Output: pass


Input: Claim: CRISPR technology allows precise editing of specific genes. [SEP] Text: 2G); one shoot was pale green that failed to develop roots; and the ten remaining plantlets were phenotypically similar to wild type. Due to loss of plants growing in soil, only 11 plantlets were collected to verify transformation by PCR. Transformation efficiencies for all constructs are indicated in Additional file 3: Table S1, the highest being 7%. Mutations were detected in T0 GmPDS8 and GmPDS9 plants, in both PDS genesWe selected 11 GmPDS8 T0 plants for sequencing, of which 10 were positive for transgene detection. Two plants developed from the same explant (#6A, #6C), and the rest were all independent lines, denoted by different numbers. Mutations were detected in 9 out of 10 transgenic plants in both PDS genes, corresponding to 90% mutation efficiency (Table 2, Additional file 4: Table S2). Interestingly, plants with visible mutant phenotypes had higher proportions of clones that showed gene editing, compared to those with wild type phenotypes. Specifically, plant #6C exhibited strong dwarf and albino phenotypes and all sequenced clones had mutations at target loci in both PDS genes, equivalent to 100% indel frequencies. Plant #7 and #10 also developed strong mutant phenotypes, they had 70% and 61% indel frequencies in GmPDS18g, as well as 52% and 68% indel frequencies in GmPDS11g, respectively. Plant #3 and #12 were partially dwarf, with albino leaves; 46% and 60% of clones showed mutations in GmPDS18g, as well as 39% and 29% of clones with mutations in GmPDS11g, respectively. Plant #5 was not dwarf, but had variegated leaves. It had 65% and 64% indel frequencies in GmPDS18g and GmPDS11g, respectively. Other plants exhibiting wild type phenotypes had between 4 to 15% indel frequencies in GmPDS18g, and 3% to 13% in GmPDS11g. We sequenced six independent GmPDS9 T0 plants. Out of the five plants verified for transformation, four had mutations in both PDS genes, and one had mutation only in GmPDS11g.

Output: corroborate


Input: Claim: Urban agriculture alone can fully meet the food demands of major cities. [SEP] Text: If from aquifers, is the seasonal discharge balanced by recharge so as to sustain water supplies and prevent subsidence as may occur? If subsidence were to take place, there can be additional problems that affect a population that were discussed in a previous 6. 4 and GMO to Food security for citizens from farm crops can be abetted by the use of agricultural chemicals (fertilizers) that replenish the nutrient content of soils depleted by a previous crop. The application of herbicides protects crops from weeds that take up nutrients while pesticides repel pests (insects, animals) that infect or consume crops. The judicious use of an optimum amount of pesticides, herbicides, and fertilizers on in-soil, bush, and tree crops will assure full growth and maximum crop yield and limit their effects on any excess that may access ecosystems. That there is no overuse is essential. It is also economically advantageous to a farmer by saving on agricultural chemicals expenses. Overuse of these chemicals can result in runoff of an excess into nearby surface waters when it rains, or after irrigation, and can also result in seepage of the chemicals and biocides into aquifers thus contaminating groundwater that may flow towards cities and be used by urbanites. Contaminated groundwater that discharges into waterways can affect the life forms inhabiting them to the detriment of society by harming an important food source. For example, runoff of nutrient rich agricultural chemicals into waterways will contribute to algal blooms that can be responsible for great fish kills (red tide) in oceans, estuaries, lakes and rivers as phytoplankton comprising the bloom die and release toxins that attack fish gills. Red tide also causes closure of shellfish beds for harvest and may cause skin problems and respiratory distress in people in coastal zones from wind borne toxins. As important is the fact that decomposition of dead organisms (mainly algae) in marine and terrestrial water bodies can use all of a habitat’s oxygen (eutrophication) thus causing fish kills and dead zones. Such actions reduce the yield of food fish for cities and for rural coastal populations. 6. 4. 1 FoodsGenetic modifications can produce seeds that may protect farm crops from weeds and repel pests that harm crops or diminish yields thereby avoiding the application of chemicals to do the job.

Output: contrast


Input: Claim: Certain claims suggest that advanced algorithms might predict emotions based on brain scans. [SEP] Text: Lastly, the distribution of insurance claims for smoking status and gender indicates that most claims are filed by non-smokers, and the frequency of filing claims is not notably affected by the policyholder’s gender (Figure 8). Display full sizeFigure 7. Numeric based on smokers. A. Histogram of age; B. histogram of BMI; C. histogram of blood pressure; D. histogram of children; E. histogram of claimDisplay full sizeFigure 8. Graphical presentation of insurance claims by smokers and non-smokersIt is observed that most non-smokers file for claims, while smokers are comparatively less likely to file a claim, and the sex of the policyholders does not matter the same (Figure 8). There is no significant relationship between charges and age or blood pressure (Figure 9). However, higher charges are associated with a higher BMI and smoking status. Furthermore, there is no distinct trend in the number of children in charge. The information in this dataset, which includes details on age, gender, BMI, blood pressure, diabetes status, number of children, smoking status, and region, offers useful insights into the demographic trends of people who file insurance claims. Determining which populations most urgently want assistance can be used to help corporations and the government make decisions. It is ideally suited for research and ML applications like predictive analytics. Increased computing power: the rise of an extensive environment of new analytics products is a phenomenon. Display full sizeFigure 9. Scatter plot of insurance claims. A. Age; B. BMI; C. blood pressure; D. children. However, it is challenging to choose the optimum model based on the evaluation metrics listed in Table 5, since certain metrics can be more pertinent in various situations. Table 5. Performance measures of algorithmsPerformance measures-square0. 100. 570. 770. 680. 790. 31Adjusted R-square0. 090. 570. 770. 680. 780. 30Mean square error (MSE)149,194,459. 2258,612,767. 5230,736,317. 1043,614,936. 7429,099,812. 4994,609,424. 94Root MSE (RMSE)12,214. 527,595. 895,544. 036,604. 165,394. 429,726. 74Mean absolute error (MAE)8,188.

Output: pass


Input: Claim: CRISPR technology allows precise editing of specific genes. [SEP] Text: The combined mutation frequency was 90% for both loci (Table 2). Similar to GmPDS8 plants, higher indel frequencies were observed in plants with strong mutant phenotypes (Additional file 4: Table S2). Plant #12 and #14 developed albino shoots that could not form roots. In both cases, mutations were detected in all sequenced clones for both PDS genes (100% indel frequencies). Interestingly, plant #12 had the same mutation in GmPDS18g, which is 1-nt insertion at 2-bp upstream of PAM (Fig. 5). Plant #5 and #15 had variegated and partially albino leaves. These 2 plants had 27% and 67% indel frequencies in GmPDS18g, as well as 85% and 88% indel frequencies in GmPDS11g, respectively. Similar to plant #12, plant #5 had the same 7-nt deletion a few bp upstream of PAM in GmPDS11g. Plant #6 exhibited phenotypes similar to wild type, only one clone showed a 2-nt deletion in GmPDS11g, while no mutation was detected in GmPDS18g. Together, these findings demonstrate that a single guide sequence at conserved region can simultaneously induce mutations in both PDS genes, and the severity of mutant phenotypes relates to indel frequencies. Again, wild type controls as well as the GmPDS8 and GmPDS9 plants negative for transgene detection did not show sequence change in both PDS genes, indicating absence of confounding basal mutations (Additional file 4: Table S2). The majority of transgenic plants had multiple mutations at each target site. Both insertions and deletions were detected. Similar to plants transformed with other genome editing constructs, mutations in GmPDS8 and GmPDS9 T0 plants were predominantly small deletions within the guide RNA regions, occurring one to several nucleotides upstream of PAM (Fig. 4, 5). In some cases, large deletions of over 15-nt encompassing PAM were detected. One-nt insertions at 2–3 bp upstream of PAM were also common, although less frequent compared to deletions (Figs. 4, 5).

Output: corroborate


Input: Claim: Urban agriculture alone can fully meet the food demands of major cities. [SEP] Text: This eliminates chemical residues on vegetables and fruits, that if not thoroughly washed, can enter the human food chain and potentially be harmful to consumers. However, ingestion of GMO grown products could be a risk to human health as suggested by controlled experiments. In these, rats developed lesions, suffered organ damage, and died after consuming GMO grown potatoes. However, a critical review of the literature suggested that the published research left an incomplete evaluation regarding the safety (toxicity) of GM crops eaten by humans and fed to animals. This is because there was no unified experimental methods so that reports could not be properly reviewed, and perhaps more important, experiments could not be repeated, a key to validation of experimental results [4]. There have been failures in GM grown corn that contributes to mutated, resistant insects that attack GM growing crops and pesticide protected crops. For example, the rootworm that infected corn developed a resistance to GMO corn treated with Bacillus thuringiensis (BT) [5, 6]. In a sense, this can be likened to the overuse of antibiotics in cattle feed consumed in feedlots that resulted in the mutation of bacteria to strains resistant to antibiotic therapy. There is the fear that during pollination of GM crops, the pollen will be carried to non-GMO fields and affect the purity of their crops. In Capulalpam, Mexico scientists documented the discovery of transgenic genes in the Mexican native corn. In 2013 Mexico banned the entry of GM corn. It is because of uncertainty of their effects on human and animal health and food security that GM crops are not allowed in the European Union, several nations in Africa, and elsewhere. In addition, some researchers believe that there is the potential for an allergic reaction in humans from ingestion of GM based corn products. Organically grown foodstuffs obviate the chemicals or GMs problems but do not produce the mass of crops needed to feed large and growing global and urban populations as was the case for the GMO “green revolution” that allowed many countries to improve their food security. 6. 4. 2 Microbes to Microbes associated with plants from biomes on all continents except Antarctica have been studied in great detail and some identified as to the characteristic they give to plants that assist agricultural projects. These have been cultured, batch produced, and used to coat seeds.

Output: contrast


Input: Claim: Certain claims suggest that advanced algorithms might predict emotions based on brain scans. [SEP] Text: 165,170. 154,066. 945,072. 643,870. 036,769. 37Mean absolute percentage error (MAPE)1. 010. 720. 660. 710. 630. 98Display full sizeAccording to the performance measures, the XGBoost and RF models have the highest R-squared with adjusted R-squared values of 0. 78 and 0. 77, respectively, which together indicate their ability to capture a significant share of the variance in the data. The XGBoost model has the lowest MSE of 29,099,812. 49, RMSE of 5,394. 42, and MAE of 3,870. 03 among the models considered, demonstrating that it has the lowest relative prediction error compared with the other models (Table 5). Furthermore, the XGBoost model recorded a MAPE of 0. 63, while the RF model recorded 0. 66, implying the lowest relative prediction error among the models taken into consideration. Moreover, both the RF and XGboost models appear to perform better than the rest of the models. The XGboost model has the highest R-squared and adjusted R-squared values and the lowest RMSE and MAE of the other models, indicating a superior fit to the data. Similarly, the RF model demonstrated low RMSE and MAE with high R-squared and adjusted R-squared values, and these indicators point to the commendable performance of the model. In terms of the XGboost model’s evaluation, the following values of R-squared, adjusted R-squared, and MAPE are 0. 79, 0. 78, 29,099,812. 49, 5,394. 42, 3,870. 03, and 0. 63, respectively, outperformed the RF model compared to other models. The above results are displayed in Table 5. The XGBoost model is the better-performing model when compared to the other model. Before selecting the ideal model, it is crucial to consider additional aspects, including model complexity, interpretability, and computing time. As a result, to forecast a customer’s insurance claim, an empirical analysis is conducted. There are six different ML algorithms used to build the model. A finance firm can successfully use the XGboost approach to anticipate a customer’s insurance claim.

Output: pass


Input: Claim: CRISPR technology allows precise editing of specific genes. [SEP] Text: In three GmPDS8 plants, 1-nt substitution, or a combination of mutation types were observed (Fig. 4). Fig. 4Representative mutations at target sites in GmPDS8 T0 plants. Individual plant harboring the mutation is indicated to the right of each sequence. Wild type sequence is shown at the top with the 20-nt guide sequence in blue and PAM sequence in green. Mutations are shown in red. The number of mutated nucleotides is indicated to the right of each sequence. -: deletion, + : insertion, S: substitution. The number of clones for each mutation is indicated in bracketsFull size imageFig. 5Representative mutations at target sites in GmPDS9 T0 plants. Individual plant harboring the mutation is indicated to the right of each sequence. Wild type sequence is shown at the top with the 20-nt guide sequence in blue and PAM sequence in green. Mutations are shown in red. The number of mutated nucleotides is indicated to the right of each sequence. -: deletion, + : insertion. The number of clones for each mutation is indicated in bracketsFull size imageSimultaneous targeting of both PDS genes did not induce mutations in several potential off-target sitesTo further examine the specificity of PDS gene targeting, we performed off-target analysis in two GmPDS8 T0 plants with visible mutant phenotypes: #5 and #6C. By using the 20-nt guide RNA sequence as query in BLAST search, potential off-target loci were identified in two homologous auxin response factor genes (Glyma. 10g053500 and Glyma. 13g140600) as well as two homologous genes (Glyma. 10g221500 and Glyma. 20g170000). They are hereafter referred as ARF10, ARF13, GGT10, and GGT20, respectively. It is worth noting that all of these sites are followed by PAM ‘AGG’. ARF10 and ARF13 contain 5 and 10 consecutive mismatches to GmPDS8 target sequence, located immediately upstream of PAM. GGT10 and GGT20 have 7 and 6 interspaced mismatches, respectively; both contain 4 consecutive mismatches directly upstream of PAM (Additional file 6, Table S4).

Output: corroborate


Input: Claim: Urban agriculture alone can fully meet the food demands of major cities. [SEP] Text: The first product of this effort, Indigo Cotton™, cotton seeds coated with a proprietary mix of microbes (bacteria and fungi) were sown in in 2016. This resulted in an 11% improvement in yield by protecting the crop against drought stress [7]. Similarly treated seeds of soy, rice, wheat and corn coated with proprietary microbe mixtures have been produced with like results. This adds to the food security of city and mega-city populations dependent on foods from outside the urban locations, complementing advances in natural hybridization and GMO that impart seed properties that protect crop yield. The company is working on microbial products that can reduce the need for nitrogen fertilizer and that offer protection against pests. 6. 5 Wastes: A Threat to Unless Used, Controlled, or Disposed of SecurelyThe demand for food is rising worldwide with increasing populations, and where incomes are also increasing, the demand for meat is rising as well. For example, the Chinese population increased by more than 40% from 1980 to 2015 and the income has increased significantly more. This resulted in a fivefold increase in the demand for pork. These changes put pressure on the animal husbandry industry to produce more product, ofttimes at a faster rate, using chemicals and vaccines. The problems that exist in this industrial production mode and solutions to them are discussed in the following paragraphs. 6. 5. 1 Problems that Affect PeopleAnother major food security concern for growing urban (and global) populations are problems with animal husbandry during growth and after slaughter and distribution. It is most threatening to ecosystems close to where thousands to millions of animals are bred in close quarters (e. g. , cattle feed lots and commercial chicken farms, respectively) and where they are taken for slaughter. The problems are how to capture and control the wastes and how to safely use them or dispose of them so as not to contaminate soils and waterways or aquifers. These are manure and urine from cattle (plus pigs, sheep, and goats) and fecal matter from chickens (plus ducks, turkeys). Added to this are slaughter house wastes (fluids [blood, wash water]) and solids (heads, innards, skins, bones, feathers), plus pathogens (e. g. , salmonella, E. Coli, listeria, coronavirus, foot and mouth disease) from dressing the food animals.

Output: contrast


Input: Claim: Certain claims suggest that advanced algorithms might predict emotions based on brain scans. [SEP] Text: By computing feature importance, the algorithm determines each feature’s contribution to USA insurance claim prediction. By computing feature importance, the algorithm determines each feature’s contribution to USA insurance claim prediction. The significance of every feature in the extension of the predictive models for the insurance claims featured in the study (Figures 10, 11, and 12). A greater value indicates the greater significance of the feature in the model and the relative weights of the explanatory factors that have the greatest influence on forecasting insurance claims. Therefore, it can be concluded that the main feature or variable is the same for the DT, RF, and XGBoost models, but their rankings vary slightly. In this dataset, smoking is a very significant factor for insurance claims in the USA, which is observed in the mentioned three models; BMI and blood pressure value are also key features and significantly impact those models. Age, children, and region have relatively insignificant impacts on the model selection for this dataset. In addition, the comparative influence of each feature target is standardized so that the cumulative sum equals 100%, with a higher value indicating a significant impact on the response variable. Smoking has the highest influence on predicting insurance claims for the RF, XGBoost, and DT models (Figures 10–12). LR, RF, and XGBoost show better claim prediction than the SVM, DT, and KNN, but XGBoost has the best performance among the six models for claim prediction (Table 5 and Figure 12). This methodology can also help review and reduce the company’s budget for insurance coverage. Display full sizeFigure 10. Feature importance of DT modelDisplay full sizeFigure 11. Feature importance of RF modelDisplay full sizeFigure 12. Feature importance of XGBoost modelThe result showed that smoking status accounted for a greater share of the explanatory variation than other variables, making it a significant factor in predicting insurance claims. This demonstrates how smoking status must be considered when creating insurance policies and pricing schemes in the USA. DiscussionInsurers can automate data processing with AI algorithms, improving efficiency and reducing errors. Insurance claim analysis of the dataset is performed on six ML models. For the dataset used, XGBoost resulted in the best prediction of an efficient insurance claim process for customer behavior and could be used for better anticipation of claim amounts. Then the next best performance model is RF.

Output: pass


Input: Claim: CRISPR technology allows precise editing of specific genes. [SEP] Text: No mutation at those sites was detected (Additional file 6: table S4), indicating high specificity for PDS gene editing. /Cas9-induced mutations and altered phenotypes were inherited in T1 generationTo examine whether gene editing induced byCas9 can be passed down to the next generation, T1 plants from three GmPDS8 lines were analyzed. Because of limited amount of seeds produced from T0 plants, all T1 seeds from GmPDS8 line #3 (1), #5 (7), #8 (2), #13 (5), and #15 (8) were planted in soil, with respective quantities for each line indicated in brackets. Due to developmental defects, seeds from line #3 and #8 did not germinate. A total of six T1 line #5 plants grew in soil, among which three (#5–1, 5–2, 5–4) exhibited strong dwarf and albino phenotypes, while others (#5–3, 5–5, 5–6) had phenotypes indistinguishable from wild type (Fig. 6). To detect the presence of transgene in this generation, PCR analysis was conducted using two sets of construct-specific primers (Additional file 7: Table S5). The first set amplified a 885-bp fragment described earlier. The second set amplified a 1117-bp fragment containing part of Cas9 and eGFP. The presence of transgene was only detected in the three plants with strong mutant phenotypes (Table 3, Additional file 8: Figure S3). Consistent with these findings, mutations were detected in all sequenced clones for both PDS genes in plant #5–2 and 5–4 (100% indel frequencies). Plant #5–1 had 100% and 93% indel frequencies in GmPDS18g and GmPDS11g, respectively (Table 3, Additional file 5: Table S3). Similar to the T0 generation, the vast majority were small deletions upstream of PAM. Longer deletions of up to 65 nucleotides were observed as well. One-nt insertions were also detected. More rarely, 1-nt substitution and 39-nt insertion were observed in single clones (Fig. 7). Interestingly, all GmPDS18g fragments from plant #5–1 shared the same 18-nt deletion upstream of and within PAM.

Output: corroborate


Input: Claim: Urban agriculture alone can fully meet the food demands of major cities. [SEP] Text: If these wastes are not collected and put to use by manufacturers or not disposed of securely to prevent interaction with the environment, they can pollute and diminish food production and contaminate natural resources in terrestrial and aqueous ecosystems. This may be by rainwater runoff of fecal matter rich in nutrient into food fish habitats (e. g. , oceans, estuaries, rivers ). The nutrient rich runoff fuels algal blooms that poison habitats (with toxins) or cause depletion of oxygen (eutrophication). As cited previously, both toxins and eutrophication can result in great fish kills. Also, leakage of pollutants in waters from animal husbandry locales into soils can contaminate crops. This might be by unregulated disposal of solid matter that allows rainwater to interact with soils and as previously noted, move dissolved contaminants into soils and by seepage through soils into aquifers thereby contaminating them. As noted in an earlier paragraph, free range stock will not cause such environmental harm when herds are properly tended (e. g. , prevent overgrazing) but will have fewer but organically bred food animals to sell. 6. 5. 2 of the Problem and Possible SolutionsTo appreciate the extent of the animal husbandry waste problem, we can examine the issue with thousands and thousands of tons of manure generated at cattle feedlots. Each head of cattle in a feedlot can drop 15–20 times the mass of manure as does one person. A lactating dairy cow can excrete ~44 times a person’s output [8]. Thus, a feedlot with 50,000 cattle would excrete the same mass of manure daily of about 800,000 people. There are 32 such lots licensed in Kansas, USA, state with well over 2,000,000 heads of cattle in feedlots. The sheer mass and volume of manure that has to be disposed of and well cleansed of pathogens and residues of growth hormones (anabolic steroids) and antibiotics used in animal husbandry. This can be accomplished in three ways. Done properly, this can reduce the risk of contamination of water and soils that can negatively affect food delivered to urban centers as well as clean water security, and limit the evolution of antibiotic resistant strains of bacteria that threaten the healthcare community, topics that will be treated in following paragraphs.

Output: contrast


Input: Claim: Certain claims suggest that advanced algorithms might predict emotions based on brain scans. [SEP] Text: To anticipate insurance claims more accurately, this study analyzes numerous variables, including smoking, that affect insurance claims across the USA. However, demographics, medical history, lifestyle and behavior, and policy details are important determinants for predicting insurance claims. These characteristics can help to anticipate claims, make appropriate decisions, and reveal insureds’ risk profiles. The degree of accuracy of the data acquired and the privacy concerns of individuals must be balanced. Responsible AI can improve the accuracy of claim processing as well as anticipate a customer’s claim in the USA. If it is not used responsibly, then it can cause bias. As a result, it is crucial to assess an AI model’s performance not only on its accuracy but also on its fairness and transparency. The use of AI for the analysis of health insurance claim data can impact the accuracy of claim processing. Therefore, to avoid biases and discrimination in the processing of insurance claims, it is necessary to think carefully about the responsible use of AI. AI algorithms can identify trends in insurance claim data and determine individuals who will need more medical care in the future. Insurance companies could use this data to modify their pricing and policy designs to more effectively satisfy their clients’ demands. Nevertheless, to prevent possible negative impacts on patients and medical professionals, it is crucial to ensure that the use of predictive models in healthcare insurance is done responsibly and ethically. Health insurance claims processing can benefit from AI and predictive models. To protect insured people’s rights, ethical considerations are crucial. Fairness, openness, data privacy, and accountability should guide model development and deployment. Insurers can use predictive modeling to preserve ethical norms and build confidence by addressing these ethical problems. The use of responsible AI in analyzing health insurance claims data and predicting healthcare utilization patterns can significantly impact the accuracy of claims processing, health insurance pricing, and policy design in the USA. Through performance measurement and feature importance analysis, the XGBoost model outperforms the best model to ensure accurate predictions over the rest of the algorithms, the role of smoking status, blood pressure, and BMI predicted insurance claims, underscoring their importance in risk assessment and policy pricing. The selection of the appropriate model should also include model complexity and computational complexity. The output of the models can assist insurance providers in making deft pricing and policy design choices, resulting in more effective and efficient healthcare delivery.

Output: pass


Input: Claim: CRISPR technology allows precise editing of specific genes. [SEP] Text: The 20-nt target sequence is highlighted in blue, PAM sequence is indicated in the green box, and mutations are circled in red. B Representative mutations at target sites on chromosome 18 and chromosome 11. Individual T1 plant harboring the mutation is indicated to the right of each sequence. Wild type sequence is shown at the top with the 20-nt guide sequence in blue and PAM sequence in green. Mutations are shown in red. The number of mutated nucleotides is indicated to the right of each sequence. -: deletion, + : insertion, S: substitution. The number of clones for each mutation is indicated in bracketsFull size imageAll T1 line #13 and #15 seeds germinated and developed into plants showing wild type phenotypes. The transgene was not detected in these plants. Targeted fragments from plant #13–1, 13–2, 13–3, 15–1, 15–2, 15–3, and 15–4 were sequenced, and no mutation was detected (Additional file 5: Table S3). DiscussionIn recent years,Cas9-mediated genome editing has been employed in soybean to knock down genes involved in various traits, such as fatty acid and storage protein synthesis, plant height, node, stem, and flowering development, as well as altering ALS1 gene for herbicide resistance [27, 30,31,32,33,34, 36, 38]. Plants with altered traits were obtained, demonstrating the potential of using this technology for crop trait improvement. Nevertheless, utilization of genome editing in soybean is still not widespread, largely due to difficulties with genetic transformation or low mutation efficiencies. Several groups have successfully mutagenized the PDS gene in Arabidopsis, rice, apple, tomato, grape, melon, cassava, etc. , usingCas9 [13, 15, 18, 19, 41,42,43]. Similar work was conducted in soybean by Du et al. [21] using cv. Jack. The authors targeted each PDS gene specifically as well as both simultaneously. Different from our research, most of their constructs were assessed in hairy roots. One construct (D7) targeting both PDS genes was selected for stable transformation using cotyledonary nodes derived from 5-day-old seedlings as explants.

Output: corroborate


Input: Claim: Urban agriculture alone can fully meet the food demands of major cities. [SEP] Text: Pigs and sheep raised in close quarters and that are infused with growth hormones and antibiotics generate masses of solid wastes that should be treated as described below for cattle. An initial disposal method used was to spread raw manure over acreage with its contained pathogens and residues of growth hormones and antibiotics. Mobilization of these pollutants by rainwater, melting snow, or floodwater has contaminated nearby surface waters by inflow, and via leakage into soils and seepage through soils into aquifers. Ingestion of these residues from soil grown and irrigated foodstuffs that are not thoroughly washed can be health threatening over time to consumers (by bioaccumulation in body organs). In the end, the volume of manure generated daily overwhelmed the available acreage and required the use of other disposal methods that would not endanger people and ecosystems. Planning teams for building a new city have to determine possible health risks may originate from previous use of what appear to be good terrain for development but that may have been for animal husbandry If so, the teams have to assess how and where wastes were disposed of and the efficiency of such disposal. One disposal method uses heat generated by manure fermentation to kill pathogens at or close to the waste accumulation site. Masses of manure are stacked up and with time ferment and heat up from within to temperatures that eliminate pathogens, growth hormones and antibiotics (>131 °F but <160 °F for 15 days). Higher temperatures will kill beneficial microbes. A problem with this method is that the high temperatures do not reach the outer edges of the stacks leaving a significant amount of the contaminants active [9, 10]. These would have to be retreated. Another fermentation method to cleanse cattle manure is to compost it in large rotatable drums that hold thousands of pounds of manure that are turned once a week for six weeks. This mixes and aerates the manure thus distributing the built up heat (>131 °F but <160 °F) throughout the mass eliminating >90% of the health threatening components. In this way, the tonnage of manure changed to compost is reduced by ~60%. The sterilized nutrient rich manure product can be dried, bagged, and sold as fertilizer that also enhances moisture retention by soils. The manure product can also be dried, pressed into briquets and combusted to produce energy [9, 10]. This can be an economic benefit to feedlot owners. Chickens produce an average of 0. 054 pound of manure daily [8].

Output: contrast


Input: Claim: Certain claims suggest that advanced algorithms might predict emotions based on brain scans. [SEP] Text: This study demonstrates how the results of these models can help insurance companies make wise decisions about pricing and policy design, leading to more effective and efficient healthcare delivery. It is crucial to ensure justice, transparency, and accountability during the development and deployment of these models to prevent any biased results. Predictive modeling and AI have enormous potential applications in the healthcare sector, but it is also crucial to uphold ethical and responsible standards. In conclusion, the healthcare sector in the USA could benefit significantly from the prudent use of AI for insurance claim forecasting. This study also has some limitations. First, small sample sizes increase sampling bias because the data may not accurately represent the population. This can affect claim processing and prediction accuracy. It is crucial to remember that the study only looked at some variables and might not have adequately reflected the full complexity of variables that influence insurance claims. The model can detect more population patterns and variability with a larger sample size. Second, data privacy is essential in insurance claim data analysis. Insurers are in charge of handling personal, financial, and health data. Insurers should observe strong data privacy rules to ensure data confidentiality and security. Analyzing multiple variables helps predict insurance claims. Sociodemographic criteria, medical history, lifestyle and behavior, and policy details are important variables that depend on the insurance type and data. Therefore, these characteristics can reveal insured persons’ risk profiles and anticipate insurance claims. It is crucial to balance the level of insurance claim data and uphold individual privacy concerns. Furthermore, it is critical to consider any potential moral dilemmas brought on by the application of such predictive models. There can also be opportunities to size and apply advanced ML techniques to analyze and improve the current models. Third, more data must be gathered to increase the sample size and boost the model’s precision. Lastly, to develop a more accurate model, it is needed to investigate more external variables, such as economic indicators, that might affect the target variable and monitor performance over time to ensure its accuracy. The future scope of the research involves employing more ML models to discover the best AI model to predict claim success or failure and compare predictions to the actual results of insurance claims.

Output: pass


Input: Claim: CRISPR technology allows precise editing of specific genes. [SEP] Text: Adventitious buds were regenerated, of which 5 out of 16 buds had dwarf and albino phenotypes, but the rest turned out to be false positives. Fully regenerated plants were not recovered in that study. We used ‘half-seed’ explants dissected from overnight-imbibed seeds for transformation of cv. Williams 82, based on the improved methodology described by Paz et al. [49]. T0 plants harboring mutations at desired loci were regenerated for all five constructs. Our genetic transformation system was reliable, with low occurrence of escapes overall. Transformation efficiency was as high as 7%. Very recently, Zhang et al. [37] also used similar transformation procedures for cv. Williams 82, and obtained a large number of transgenic plants. et al. [21] and Zhang et al. [37] used one guide RNA to induce mutations in the two PDS genes, similar to our GmPDS8 and GmPDS9 constructs. However, neither group evaluated targeting specificity as well as transmission of gene modifications beyond the T0 generation. Using simple constructs, we demonstrated efficient and specific editing of PDS genes in stably transformed soybean plants. Mutations and the associated phenotypes were transmitted to T1 progenies. Our simple and reliable system can be used as a reference to modify other genes for soybean trait improvement, contributing to the advancement ofCas9-mediated genome editing in soybean. We obtained 75% to 100% mutation efficiencies for the five constructs. A few transgenic plants did not show mutations at target loci, likely because Cas9-induced DSB failed to take place, or the cleavage was correctly repaired by cellular DNA repair mechanisms. Observed mutations typically occurred a few nucleotides upstream of PAM, consistent with the location of Cas9-induced DSB [7, 9]. The vast majority were small deletions, although 1-nt insertion was also common. These indel types corroborate with the findings reported in earlier publications [33, 34, 36, 37]. As the guide sequences fall within the coding regions, such mutations caused missing amino acids, or frame shift, leading to altered amino acid sequences or premature termination of peptide synthesis. Indel frequencies varied among individual plants, with higher frequencies in plants exhibiting mutant phenotypes, consistent with the findings reported by Zhang et al. [37].

Output: corroborate


Input: Claim: Urban agriculture alone can fully meet the food demands of major cities. [SEP] Text: A commercial operation with one million chickens would produce 27 lbs. (12 1/4 kg) of manure daily or 54 lbs. (24. 5 kg) daily for two million chickens. The manure is nutrient rich (nitrogen and phosphorus) but is a carrier of disease and internal parasites. When this is spread on fields as a disposal method, runoff during rainstorms can carry the waste to discharge into productive rivers estuaries, and oceans that may be serving the interests of urban populations. As discussed earlier, the nutrient rich matter stimulates algal and toxic dinoflagellates growth. When algae die, they decompose using oxygen in the water to the point where there is no oxygen for fish and a resulting massive fish kill including oysters and clams. When toxic dinoflagellates die, they release a neurotoxin into the water that manifests itself in the ocean as a “red tide” and millions of dead fish. This causes a break in the aqueous food web and temporarily diminishes food fish security for coastal communities (cities and towns, villages) as well as causing a temporary economic disruption for fisheries. Instead of spreading the chicken manure on fields and causing ecological and economic problems, many commercial poultry producers are composting and aging the manure for 2–3 months and then recycling it as fertilizers. chicken producer set up a large scale controlled composting operation that has profitably processed 650,000 tons (591,000 tonnes) of chicken manure (waste from more than 48 million chickens) during 16 years to produce certified organic fertilizer [11]. 6. 5. 3 Waste ProblemUrine from feedlots that is not captured and properly treated before discharging it at the surface can seep through soil into groundwater and contaminate it with the chemical nitrate. Groundwater carries the nitrate slowly down flow commonly at 1–5 ft. (30–150 cm) a day depending on the aquifer rock permeability. If there is a population 5 mi (8 km) down flow (“out of sight, out of mind”) that uses the groundwater as its primary source, a 5 ft. a day flow rate would bring the nitrate contaminated water from a feedlot to unaware users in about 14 years. If urine input were to stop, it would take 14 years for the contaminated aquifer water to clear a municipal or individual well 5 mi away.

Output: contrast


Input: Claim: Certain claims suggest that advanced algorithms might predict emotions based on brain scans. [SEP] Text: AbbreviationsAdaBoost:adaptive boostingAI:artificial intelligenceBMI:body mass indexDT:decision treeEDA:exploratory data analysisKNN:k-nearest neighborsLR:linear regressionMAE:mean absolute errorMAPE:mean absolute percentage errorML:machine learningMSE:mean square errorRF:random forestRMSE:root mean square errorSVM:support vector machineXGBoost:extreme gradient boosting DeclarationsAuthor contributionsAA: Conceptualization, Data curation, Formal analysis, Methodology, Software, Writing—original draft, Writing—review & editing. VRP: Supervision, Validation, Writing—review & editing. All authors read and approved the submitted version. Conflicts of interestThe authors declare that they have no conflicts of interest. Ethical approvalNot applicable. Consent to participateNot applicable. Consent to publicationNot applicable. Availability of data and materialsThe datasets analyzed for this study can be found in Kaggle by Shukla ( applicable. Copyright© The Author(s) 2024. 1. National health expenditure (NHE) fact sheet [Internet]. [cited 2023 Sep 3]. Available from: 2. . Demographic variation in health insurance coverage: United States, 2021. Hyattsville (MD): for Health Statistics; 2022 Nov. Report No. : 177. 3. Health costs and financing: challenges and strategies for a new administration. (Millwood). 2021;40:235–42. [DOI] [PubMed] 4. . All models are wrong, but many are useful: learning a variable’s importance by studying an entire class of prediction models simultaneously. J Res. 2019;20:177. [PubMed] [PMC]5. . Big data analytics and business intelligence in industry. Front. 2017;19:1229–32. [DOI] 6. . Global AI survey: AI proves its worth, but few scale impact [Internet]. McKinsey & Company; 1996-2024 [cited 2023 Sep 1]. Available from: 7. Jefferies D. What AI can do for the insurance industry? [Internet]. ; 2024 [cited 2023 Sep 10]. Available from: 8. The use of artificial intelligence-based innovations in the health sector in Tanzania: a scoping review. Technol. 2023;12:100728.

Output: pass


Input: Claim: CRISPR technology allows precise editing of specific genes. [SEP] Text: In a few severely dwarf and albino GmPDS8 and GmPDS9 T0 plantlets, 100% indel frequencies in both PDS genes were obtained. Whereas in GmPDS8 and GmPDS9 plants without visible mutant phenotypes, indel frequencies were low. These plants could be chimeras. Previous studies compared the targeting efficiencies using the soybean U6 promoter vs. Arabidopsis U6 promoter, and reported increased efficiency using the former [21, 23]. Evaluation of several soybean U6 promoters for mutation efficiencies was also undertaken [25]. Switching to an efficient soybean U6 promoter for sgRNA expression could further improve theCas9 system. One of the concerns withCas9 is off-target effect [50]. Although we did not perform full genome sequencing for full off-target analysis, our assessments suggested specific targeting of PDS genes. First, we sequenced both GmPDS11g and GmPDS18g fragments in examined plants. GmPDS1 and GmPDS3 target GmPDS18g specifically, each guide RNA contains 3 mismatches to the GmPDS11g counterpart. In both cases, the 3 interspaced mismatches occur at positions within 14-nt at the 3’ end of the 20-nt guide sequence. Mutation was not detected in the sequenced GmPDS11g fragments. Similarly, GmPDS7 targets GmPDS11g specifically, also with 3 interspaced mismatches to the GmPDS18g counterpart. One mismatch is 18-nt away, and two mismatches within 14-nt upstream of PAM. No mutation was detected in the GmPDS18g counterpart either. As expected, plants transformed with the constructs targeting one PDS gene specifically were phenotypically similar to wild type, as disruption in one paralogue could be functionally compensated by the other. For additional analysis, we examined several potential off-target loci outside of PDS genes, with sequence similarities to GmPDS8 guide RNA, followed by PAM ‘-NGG’. ARF10 has 5 consecutive mismatches located immediately upstream of PAM. Its homologue ARF13 contains 10 consecutive mismatches, also at the 3’ end.

Output: corroborate


Input: Claim: Urban agriculture alone can fully meet the food demands of major cities. [SEP] Text: 6 Threats to from (Anabolic Steroids) and in Animal HusbandryFor many of the ~4 billion people living in cities/mega-cities in 2018 or of the 6. 9 billion projected to inhabit them in 32 years (2050) in developed, developing, and less developed countries, meat from ruminants, foul, or fish is or will be a common food in their diets. This often comes from distant sources. Methods of production of these comestibles varies according to the standards established by health agencies charged with protecting the food supplies and security for their citizens. For some, this means disallowing the use or overuse of chemicals and/or vaccines to stimulate animal growth or as protection against diseases especially in large scale operations such as cattle feedlots, dairy farms, pig pens, commercial poultry farms, and aquaculture. This applies as well to smaller meat production set ups. Planning teams should consider food sources/security when they assess the availability of food needed to sustain people that will inhabit a purpose built city or existing cities with rapidly growing urban populations. These are discussed in the following sections. 6. 6. 1 Residues in Meat ProductsAs important as dealing with solid and liquid wastes generated in food supply businesses is dealing with the residues from growth hormones (anabolic steroids) implanted in cattle as they enter feedlots in the United States. There are three natural and three synthetic steroids in use. At slaughter houses, these are found in measurable concentrations in beef (muscle and fat), and organ meats (e. g. , liver and kidneys). These may be consumed by most urban citizens that do not opt to buy organic meat products, most often because of higher cost. In addition to beef cattle, the steroids are also allowed for use in dairy cows and sheep, but not for pigs or poultry. The use of the recombinant bovine growth hormone (rbGH) was banned in meat production in the in 1988, and subsequently in Canada, Australia, New Zealand, and Japan because the rbGH gives rise in milk to IGF-1, a chemical that helps some types of cells to grow and may influence the risk of prostate, breast, or colorectal cancer [13, 14]. Because the growth hormones cause unnatural cell growth, a phase in the development of cancer, it is incumbent on governments to further investigate banning their use in animal husbandry.

Output: contrast


Input: Claim: Certain claims suggest that advanced algorithms might predict emotions based on brain scans. [SEP] Text: [DOI] 9. . Artificial intelligence in insurance sector. J Soc. 2019;21:79–91. 10. . artificial intelligence strategy: implications and challenges for digital health. Health. 2020;2:e376–9. [DOI] [PubMed] 11. Minssen T, Gerke S. Ethical and legal challenges of digital medicine in pandemics. In: editors. Pandemics and ethics: development – problems – solutions. Berlin, Heidelberg: Heidelberg; 2023. 202. [DOI] 12. . Responsible artificial intelligence in healthcare: predicting and preventing insurance claim denials for economic and social wellbeing. Front. 2023;25:2179–95. [DOI] 13. . Role of risks in the development of responsible artificial intelligence in the digital healthcare domain. Front. 2023;25:2257–74. [DOI] 14. Brundage M. Artificial intelligence and responsible innovation. In: Müller VC, editor. Fundamental issues of artificial intelligence. Cham: Publishing; 2016. 54. [DOI] 15. . Fraud detection and analysis for insurance claim using machine learning. In: 2022 on Signal Processing, Informatics, Communication and (). on Signal Processing, Informatics, Communication and (); 2022 Mar 10-12; Thiruvananthapuram, India. IEEE; 2022. 11. [DOI] 16. Biddle J. Do high claim-denial rates discourage claiming? Evidence from workers compensation insurance. J Risk Insur. 2001;68:631–58. [DOI] 17. . Analysis of effectiveness of apriori algorithm in medical billing data mining. In: 2008 4th on Emerging Technologies. on 2008 Oct 18-19; Rawalpindi, Pakistan. IEEE; 2008. 31. [DOI] 18. . A backtesting protocol in the era of machine learning. J Sci. 2019;1:64–74. [DOI] 19. Buchanan BG. Artificial intelligence in finance [Internet]. CC BY; [cited 2023 Sep 17]. Available from: 20. . Comparison of the primitive classifiers with extreme learning machine in credit scoring. In: 2009 on. on 2009 Dec 08-11; Hong Kong, China. IEEE; 2009. 8.

Output: pass