Input: Claim: Climate change is causing an increase in the frequency of extreme weather events. [SEP] Text: -19 PreprintsProtocolsVideosJournalsTools & a 10. 21203/rs. 3. rs-4542321/v1This work is licensed under a CC BY 4. 0 LicenseStatus:Under ReviewVersion 1posted You are reading this latest preprint versionAbstractClimate change is creating more frequent extreme weather events. Yet the impacts of such events on human behavior, specifically violence, are not well understood. We used Wayne County, Michigan, as a case study to explore extreme weather’s influence on violence. We gathered county data on extreme weather events, firearm violence, and child maltreatment at the daily level from 2018-2023. Over this period, the week following an extreme weather event had less firearm violence (RR: 0. 74[0. 57-0. 98]); analyses found no associations with child maltreatment (RR: 1. 02[0. 89-1. 17]). Yet, between March 2020-2021—a year of strained resources—analyses found no protective association against firearm violence (RR: 1. 02[0. 74, 1. 41]), and the week following an extreme weather event had more child maltreatment (RR: 1. 18[0. 97-1. 44]). The influence of extreme weather on constraining people’s activities towards their homes may explain the decreased risk for firearm violence following an extreme weather event. Associations between extreme weather and child maltreatment, however, are likely products of compounded caregiver stress. Mitigating the adverse effects of climate change on child safety should therefore involve maintaining or quickly reestablishing services to support caregivers and children before, during, and after extreme weather events. Social science/Environmental studiesScientific community and society/Social sciences/Climate change/Climate-change impactsFiguresFigure 1Figure 2Figure 3Figure 4-induced climate change is already producing extreme weather events1–5—including heat waves, flooding, and severe winds—that harm human health and well-being. 6–10 Well-known harms of extreme weather events involve morbidity and mortality directly from the physical event, such as heat stroke, injury from debris, and drowning. 6,8,10,11 Climate change-induced extreme events are also likely to damage properties and infrastructures, with impacts ranging from short-term power loss or transportation disruption to home destruction, and even permanent land loss, for the case of extreme flooding in coastal areas.

Output: corroborate


Input: Claim: Most biodegradable plastics require industrial composting facilities to break down fully. [SEP] Text: Terms and Fees. A. The term of this Agreement is _____________ ("Subscription Period"). Access to the Product is for the only. will remain in effect thereafter for successive so long as annual subscription fees, as such may change from time to time, are paid. Licensee and/or ASTM have the right to terminate this Agreement at the end of a by written notice given at least 30 days in advance. B. Fees: 8. Verification. ASTM has the right to verify compliance with this Agreement, at its expense, and at any time during the course of normal business hours. To do so, ASTM will engage an independent consultant, subject to a confidentiality agreement, to review Licensee's use of ASTM Product and/or Documents. Licensee agrees to permit access to its information and computer systems for this purpose. Verification will take place upon no less than 15 days notice, during normal business hours and in a manner that does not interfere unreasonably with Licensee's operations. If verification reveals unlicensed or prohibited use of the ASTM Products or Documents, Licensee agrees to reimburse ASTM for the costs incurred in verification and reimburse ASTM for any unlicensed/prohibited uses. By invoking this procedure, ASTM does not waive any of its rights to enforce this Agreement or to protect its intellectual property by any other means permitted by law. Licensee acknowledges and agrees that ASTM may imbed certain identifying or tracking information in the ASTM Products available on the Portal. 9. Passwords:Licensee must immediately notify ASTM of any known or suspected unauthorized use(s) of its password(s), or any known or suspected breach of security, including the loss, theft unauthorized disclosure of such password or any unauthorized access to or use of the ASTM Product. Licensee is solely responsible for maintaining the confidentiality of its password(s) and for ensuring the authorized access and use of the ASTM Product. Personal accounts/passwords may not be shared. 10. Disclaimer of Warranty: Unless specified in this Agreement, all express or implied conditions, representations and warranties, including any implied warranty of merchantability, fitness for a particular purpose or non-infringement are disclaimed, except to the extent that these disclaimers are held to be legally invalid. 11.

Output: pass


Input: Claim: Every ancient civilization has left behind detailed written records. [SEP] Text: On the second point, we cited that Malawi prioritized youth access to family planning in their Strategy 2015-2020. The same policy also highlights the importance of education and prioritizing educational attainment among adolescent girls – we just did not cite this directly in the paper. I generally found the graphics challenging to read and interpret, with the key messages not clearly represented visually. Perhaps fewer and simpler graphics could better convey the main findings. We have added interpretation to the wealth and education graphics. I’d like more discussion about implications of the findings that some advantaged groups have experienced MCP stagnation or declines. Does this imply an inequitable focus on these groups, suggesting further declines among these groups under the FP2020 “equity” approach? Unlikely, but this could still have implications about how the FP2030 defines equity moving forward. After reinforcing their message that in its aim of reaching 120 million additional users FP2020 does not seem to have widened the use gap between advantaged and disadvantaged women, I’d encourage the authors to give a bit more consideration to their findings on MCP declines among several more advantaged groups and the implications this might have for FP2030. The changes in modern contraceptive use among the most advantage groups (e. g. most education, richest, oldest, urban) were not significant. We have added this note into the discussion. Overall, we found your feedback to be incredibly helpful. Thank you for taking the time to make comments. Specific questions are addressed below. I suggest the authors focus the scope of this analysis and interpretation more specifically on the contraceptive use (or demand satisfied – see point #3) outcomes they can directly measure with DHS and MICS data used here. Though the authors say “we examine FP2020 country data and policies for signs of inequity” the data and methods in this paper do not allow it to comment directly on the focus of programs or policies. Such an analysis would require more comprehensive (not just selective) data on programmatic and policy decisions, with adequate lag time for analysis. We agree we would need additional data to discuss how program and policies impacted MCPR gains. Hence why it is not a focus of this paper and we removed any 2019. Is there a reason for using the Bangladesh 2014 DHS and not the 2017-18 survey?

Output: pass


Input: Claim: Climate change is causing an increase in the frequency of extreme weather events. [SEP] Text: 12 Although the resulting economic consequences can be quantified13 and even predicted,14,15 less is known about how the aftermath of these extreme weather events influence human behavior, specifically, violence. A nascent and growing body of research suggests that extreme weather events may increase risk of violence. 16–20 A 2013 meta-analysis found that each one-unit standard deviation change in climate toward warmer temperatures or more extreme rainfall increased violence by 4%. 17 As climate change continues, communities will experience unprecedented extreme weather events of larger magnitudes, with increased frequency, in new locations, during different times of the year, and in new combinations. 21 Together, this research suggests that climate change could have a substantial and growing influence on violent human behavior. Understanding when and how extreme weather events relate to violence is critical for developing strategies that can anticipate and reduce the harms of climate change on human health and well-being. The existing framework: offers one explanation as to how weather events may affect violence. 22,23 Initially developed to explain increases in crime between 1947-1974 in the United States, Theory posits that dispersing activities away from households and families creates opportunities for crime, thus producing higher crime rates. 23 Researchers have used this framework to explain the association between heat and elevated rates of violence by suggesting that dispersing routine activities away from the household when the weather is warm or hot increases interpersonal interactions in the community, which creates more opportunities for violence. 24,25 Prior applications of Theory to weather and violence predominantly focus on one aspect of weather, temperature, and so do not currently consider how other extreme weather events influence public safety and violence. 24,25 Although all extreme weather events can influence the locations of people’s daily activities, different types of extreme events will factor differently into people’s decisions to remain at or leave home before, during, and after an extreme weather event. 26,27 In addition, personal circumstances will also influence people’s activities following an extreme events: for example, in the days following an extreme weather event, some people may move away from interacting in the community and towards their homes and other shelters to protect against uncomfortable or dangerous conditions, while other people may engage in more interpersonal interactions with people outside their household to assess property damage and support community repair. 28–30 As such, the Theory framework may be limited in its ability to explain population-level changes in violence following extreme weather events.

Output: corroborate


Input: Claim: Most biodegradable plastics require industrial composting facilities to break down fully. [SEP] Text: Redlines save you time and ensure you see what the changes are to the standard. you select the "Standard + Redline" option you get both documents! Best of all, the cost of a Standard + Redline is only slightly more than buying the by itself. Soon! Price: Add to & and Handling × Domestic orders are delivered via Service (UPS) or (USPS). Transit times average 3 to 5 business days. Please be aware that UPS will not deliver packages to Boxes. . orders are delivered via courier post services which can be either a postal service, courier service, or a combination of both. is untraceable. Please allow 4-7 weeks for delivery. . Please be aware that carriers will not deliver packages to Boxes. Because of the variability of customs processes and procedures in different countries, ASTM International cannot guarantee transit times to international destinations. Customs duty and taxes are the responsibility of the consignee. Shipping & Handling charges follow the rate schedule, below: Shipping & Up to $50. 00 $18. 00 $50. 01 to $100. 00 $20. 00 $100. 01 to $150. 00 $28. 38 $150. 01 to $250. 00 $37. 59 $250. 01 to $500. 00 $54. 09 $500. 01 to $750. 00 $73. 48 $750. 01 to $1000. 00 $89. 57 $1000. 01 to $1500. 00 $116. 61 $1500. 01 to $2500. 00 $152. 29 $2500. 01 to $4999. 00 $201. 00 $5000. 00 to $higher $225. 00 Shipping and Handling charges are approximate. Additional charges may be incurred if your order requires multiple shipments. This does not apply to complete sets and sections. × -. By purchasing a subscription and clicking through this agreement, you are entering into a contract, and acknowledge that you have read this License Agreement, that you understand it and agree to be bound by its terms. If you do not agree to the terms of this License Agreement, promptly exit this page without entering the ASTM Product. 1. Ownership:is copyrighted, both as a compilation and as individual standards, 2. Definitions. A.

Output: pass


Input: Claim: Every ancient civilization has left behind detailed written records. [SEP] Text: Unless there is a compelling reason related to the data, using the 2017-18 survey instead will provide a longer time lapse to better measure cumulative influence of FP2020. We only included surveys that were released by June 2019 and the Bangladesh 2017-18 had not been released by June 2019. The selective citing of policies related to increases in MCP among certain groups (e. g. , Malawi’s focus on youth) distracts from the overall finding/message (that FP2020 commitments, as they were applied within countries, did not seem to exacerbate inequalities writ large). These policies are also cited inconsistently – e. g. , credited for MCP gains among Malawi youth but no such policy is cited for the substantial gains among Malawi’s uneducated women – and thus come across as selective. On the first point, the overall focus of the paper is to assess if FP2020’s 120 million goal exacerbated inequities in countries. The focus of the paper is not on the country commitments themselves. We use the Malawi example to show that countries focused on implementing policies that supported reducing inequities. On the second point, we cited that Malawi prioritized youth access to family planning in their Strategy 2015-2020. The same policy also highlights the importance of education and prioritizing educational attainment among adolescent girls – we just did not cite this directly in the paper. I generally found the graphics challenging to read and interpret, with the key messages not clearly represented visually. Perhaps fewer and simpler graphics could better convey the main findings. We have added interpretation to the wealth and education graphics. I’d like more discussion about implications of the findings that some advantaged groups have experienced MCP stagnation or declines. Does this imply an inequitable focus on these groups, suggesting further declines among these groups under the FP2020 “equity” approach? Unlikely, but this could still have implications about how the FP2030 defines equity moving forward. After reinforcing their message that in its aim of reaching 120 million additional users FP2020 does not seem to have widened the use gap between advantaged and disadvantaged women, I’d encourage the authors to give a bit more consideration to their findings on MCP declines among several more advantaged groups and the implications this might have for FP2030. The changes in modern contraceptive use among the most advantage groups (e. g. most education, richest, oldest, urban) were not significant.

Output: pass


Input: Claim: Climate change is causing an increase in the frequency of extreme weather events. [SEP] Text: 46 Systemic injustices, racism, violence, and health inequities are also entwined in the county’s past and present. Over one-fifth of the counties’ residents live in poverty. 43 Property red-lining, poor housing quality, and pollution have placed economic, social, and health burdens on residents, particularly Black and low-income residents48,49 -19 pandemic severely exacerbated existing racial disparities in housing, food insecurity, and health among residents. 50,51 Like most areas across the United States, was not prepared for the COVID-19 pandemic. Particularly in Detroit, the state’s most populous city and where over one-third of residents live,43 the pandemic strained an already stretched municipal and social infrastructure. 52,53 The city had privatized public health services in 2012 to prepare for bankruptcy, and community need for public health and economic supports during the first year of the COVID-19 pandemic far out-paced what existing services could provide. 53 County’s specific history, assets, and struggles are unique, they also reflect the more widely. As such, presents an important case study for the associations between extreme weather events and safety. In the present study, we considered extreme weather’s association with violence, including interpersonal firearm violence and child maltreatment, in Wayne County, Michigan. We evaluated how the associations between extreme weather and violence changed over time. Specifically, we evaluated these associations before the COVID-19 pandemic onset (2018-2019), during the first year of the COVID-19 pandemic (March 2020-March 2021), and immediately post-pandemic onset (2022-2023). We expected that disruption caused by an extreme weather event during the first year of the COVID-19 pandemic added stress to an already precarious situation, thereby tipping the balance of influences towards threatening safety. As such, we hypothesized that associations between extreme weather events and violence to be strongest during the first year of the COVID-19 pandemic, as compared to immediately before or after pandemic onset. of extreme weather events and violence Between 2018-2023, 158 days of extreme weather events, 4,731 firearm violence incidents, and 23,908 confirmed cases of child maltreatment occurred in Wayne County, Michigan. Figure 1 illustrates the frequency of these extreme weather events, firearm violence incidents, and confirmed cases of child maltreatment at the daily level over the study period.

Output: corroborate


Input: Claim: Most biodegradable plastics require industrial composting facilities to break down fully. [SEP] Text: Phyllosphere yeasts rapidly break down biodegradable plastics access Published: 29 November 2011 Phyllosphere yeasts rapidly break down biodegradable plastics Kitamoto1, Yukiko Shinozaki1, Xiao-hong Cao1, Tomotake Morita2, Masaaki Konishi2,5, Kanako Tago1, Hideyuki Kajiwara3, Motoo Koitabashi1, Shigenobu Yoshida1, Takashi Watanabe1, Yuka Sameshima-Yamashita1, Toshiaki Nakajima-Kambe4 & …Seiya Tsushima1 Show authors AMB Express 2. Yeast stock cultures were obtained from stock frozen at -80°C and were incubated at 30°C for 3 days on malt-yeast-glucose-peptone (YM) agar medium containing 1% glucose, 0. 5% peptone, 0. 3% yeast extract, 0. 3% malt extract and 1. 5% agar. Seed cultures were prepared by inoculating cells grown on YM agar plates into flasks containing fungal minimum medium (FMM) with 4% glucose and incubating them at 30°C on a rotary shaker at 220 rpm for 4 days; the FMM was composed of 0. 2% NaNO3, 0. 02% MgSO4, 0. 02% KH2SO4, and 0. 1% yeast extract, dissolved in tap water before being autoclaved. For solid cultures, the seed culture (200 μl) was spread on the surfaces of FMM agar plates composed of a bottom layer of FMM-agar medium (15 ml) with no carbon source and an upper layer of 1. 5% agar (5 ml) containing a carbon source comprising 1% PBSA emulsion and 1% soybean oil (Wako Chemicals, Osaka, Japan). For liquid cultures, 500-ml Erlenmeyer flasks containing 50 ml of FMM culture medium with one of the following carbon sources: 1% soybean oil, 6% glycerol, or 4% glucose, were inoculated with 500 μl of seed culture and incubated under the same culture conditions as for seed cultures.

Output: contrast


Input: Claim: Every ancient civilization has left behind detailed written records. [SEP] Text: We have added this note into the discussion. Competing Interests: No competing interests were disclosed. a concern 0 to cite this report: Malarcher S. For: No one left behind: has the pursuit of FP2020’s 120 million additional users goal left some women behind? [version 1; peer review: 2 approved with reservations]. Res 2021, 5:114 ( The direct URL for this report is: The 1. This one is easy to read. It would be more interesting to present the diff in diff analysis. I appreciate the reference and cut off according to confidence interval, but is there a way to include them in the paper? I don’t believe it is appropriate to compare the most vulnerable (poorest) with the most advantaged (wealthiest). I recommend focusing your analysis on comparing the most vulnerable to an index population (poorest with middle income), as you have done and drop the other analysis. This comparison is more appropriate in my view and could make the figures and analysis easier to communicate. This is true for education and age as well. The residential analysis doesn’t reflect on shifts in demographics. Was there a significant shift in people from rural to urban settings? I can’t follow the finding on age. Please clarify. Did you limit the analysis to married women 15-19? Did you explore using sexually active 15-19 yrs olds? The conclusion is a bit difficult to follow. It’s not just about – were there any significant gains in vulnerable populations. What we want to see is that programs focused on these groups and we saw them “catch up”. How did their gains compare with gains elsewhere? Perhaps you could start the conclusion with some general statements about which population groups saw the greatest increases in country (vulnerable or not) and then focus on the countries that show significant gains in reducing inequities. Is the work clearly and accurately presented and does it cite the current literature? the study design appropriate and is the work technically sound? sufficient details of methods and analysis provided to allow replication by others? applicable, is the statistical analysis and its interpretation appropriate? all the source data underlying the results available to ensure full reproducibility? the conclusions drawn adequately supported by the results? Interests: No competing interests were disclosed.

Output: pass


Input: Claim: Climate change is causing an increase in the frequency of extreme weather events. [SEP] Text: ( documents storms and other significant weather phenomena that have sufficient intensity to cause loss of life, injuries, substantial property damage, and/or disruption to commerce. While the database includes 48 event types including tornado, winter storm, dense smoke, or excessive heat, our analysis included all storm events listed in the database and did not differentiate between weather event types. In addition, we also leveraged the for ( to obtain daily maximum temperature from local weather stations; we averaged the daily maximum temperature values across all weather stations in Wayne County, Michigan for each day in the study period. is a publicly available online archive of gun violence incidents collected from over 7,500 law enforcement, media, government, and commercial sources daily. Researchers have previously established strong sensitivity (81. 1%) and positive predictive value (99%) of the Archive in comparison to police department data shootings in four major cities across the United States. 61 is an independent data collection and research group with no affiliation with the study team. does not distribute detailed methods on how they collect data, but their website states that they collect incident data “from over 7,500 law enforcement, media, government and commercial sources daily. ”63 As such, media reporting of firearm violence may decrease in the days following an extreme weather event, as news coverage for the event dominates reporting. To reduce this potential source of bias, we restricted analyses to 2018-2023, as sensitivity and specificity for firearm violence is higher during this period as compared to pre-2018. 61 The restricted-use child welfare data come from a state administrative dataset of child welfare case records secured through a data-sharing agreement between the Michigan child welfare system and the University of Michigan. All case records are generated by child welfare workers during their regular work duties and reflect the perceptions and judgments of those workers and/or their supervisors. The use of these records for research purposes was granted by the state agency participating in the study. Defining extreme weather events and violence Exposure. Our primary exposure was the presence (versus absence) of an extreme weather event on a given day, per the. Some extreme weather events span multiple days (range 1-30 days). To avoid categorizing an entire month as experiencing an extreme weather event, we limited extreme weather events to last a maximum of seven days for the main analyses.

Output: corroborate


Input: Claim: Biodegradable plastics will completely replace traditional plastics by 2030. [SEP] Text: Can bio-plastics replace non-biodegradable plastics? Kabir,1 × Regret for the inconvenience: we are taking measures to prevent fraudulent form submissions by extractors and page crawlers. Please type the correct Captcha word to see email ID. Hossain,2 Kazuyuki Shimizu3 1Department of and Biotechnology, University, Bangladesh2Department of Pharmacy, University, Bangladesh3Department of Bioscience and Bioinformatics, Keio University, Japan Correspondence: and Chairperson, Department of and 9666775577 Received: October 14, 2016 | Published: July 10, 2017 Citation:. Can bio-plastics replace non-biodegradable plastics? J Bioeng. 2017;3(4):381-383. DOI: 10. 15406/jabb. 2017. 03. 00074 -3-hydroxybutyrate (PHB) is widely studied and best-characterized bioplastic within polyhydroxyalkanoates family, which can be used to produce a wide range of household and packaging products as well as medical products. Although biodegradable PHB is environmental friendly and not dependent on fossil resources, its production cost has been traditionally very expensive by bacterial fermentation techniques using recombinant E. coli. The recombinant diatoms and transgenic plants have also been evaluated for efficient PHB production. But, it has proved extremely difficult to increase the PHB yield that prohibits its production at the industrial scale. To address these problems, this paper has focused on the metabolic pathway manipulations in recombinant E. coli since they lack PHB degradation pathways unlike native producers. Another advantage of using recombinant E. coli is their ability to use a wide range cheap carbon sources, accumulate large amounts of polymers with higher productivity, maintain the high-cell density fermentation and recover the PHB easily. Since no single strategy has been proved to be sufficient enough to produce PHB industrially until today, the advanced and integrated approaches have to be considered for its efficient production in order to compete with non-biodegradable petrochemical plastics. Keywords: E.

Output: contrast


Input: Claim: Every ancient civilization has left behind detailed written records. [SEP] Text: Reviewer Expertise: family planning, social science research, KM, research translation I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard, however I have significant reservations, as outlined above. . For: No one left behind: has the pursuit of FP2020’s 120 million additional users goal left some women behind? [version 1; peer review: 2 approved with reservations]. Res 2021, 5:114 ( The direct URL for this report is: This one is easy to read. It would be more interesting to present the diff in diff analysis. All countries in the wealth graphic should have two bubbles. One bubble is for the earlier survey and the second bubble is for the later survey. We opted not to do a regression analysis (which would be a difference in difference analysis) and our reasoning added to the discussion section. We will add additional notes that will help with the interpretation. I appreciate the reference and cut off according to confidence interval, but is there a way to include them in the paper? The confidence intervals are included in the paper. For interpretability of the findings, we opted to keep them in tables and not directly in text. I don’t believe it is appropriate to compare the most vulnerable (poorest) with the most advantaged (wealthiest). I recommend focusing your analysis on comparing the most vulnerable to an index population (poorest with middle income), as you have done and drop the other analysis. This comparison is more appropriate in my view and could make the figures and analysis easier to communicate. This is true for education and age as well. We wanted to compare the most disadvantaged group to the least disadvantaged group because we wanted to assess if the most vulnerable (disadvantaged) were left behind while the most advantaged continued to progress. While we focus on these two groups in most of the analysis, we do calculate MCPR among all levels of the equity dimensions and those comparisons can be made by all readers by reviewing the tables. The residential analysis doesn’t reflect on shifts in demographics. Was there a significant shift in people from rural to urban settings? We investigated this question, and we did not see any change in people moving from rural to urban settings in every country between surveys. I can’t follow the finding on age. Please clarify. Did you limit the analysis to married women 15-19?

Output: pass


Input: Claim: Climate change is causing an increase in the frequency of extreme weather events. [SEP] Text: September 01 2023 Connecting extreme weather events to climate change Advances in attribution science are improving understanding of human influence on our planet. Search for other works by this author on: PubMed 10. 1063/PT. 3. 5309 Open the PDF for in another window and Connecting extreme weather events to climate change. 1 September 2023; 76 (9): 40–46. Download citation file: Ris (Zotero) toolbar search Menu toolbar search search input Search input auto suggest filter your search his house in Oxford, UK, was flooded by an exceptionally rainy storm in January 2003, proposed that the anthropogenic influence on severe weather events could be quantified. 1 Before that, most climate scientists avoided discussing how human activity affected individual extreme weather events. Rather, they would deflect, saying, for example, “While no individual event can be tied to climate change, whatever happened is consistent with expectations. ” That statement is no longer true. Using extreme-event attribution techniques, it is now possible to make quantitative statements about the human influence on many classes of individual weather and climate events. View largeDownload slide. COM/E4CView largeDownload slide. COM/E4C Close modal In 2003, shortly after Allen’s proposal, central Europe experienced a disastrous heat wave that caused more than 70 000 excess deaths. At the time, using a high-quality record of European temperatures and a single climate model, Allen and colleagues estimated that climate change at least doubled the chances of the measured high daytime temperatures. 2 Since then, the field of extreme-weather-event attribution has expanded to include not just heat waves but also floods, droughts, heavy precipitation, and certain extreme storms, such as hurricanes (reference 3, 2017. (Courtesy of US Guard/Staff Sgt. Daniel J. Martinez. )View largeDownload slidePort Arthur, Texas, was devastated by the overwhelming amount of precipitation from in 2017. (Courtesy of US Guard/Staff Sgt. Daniel J. Martinez. ) Close modal A second technique, known as Granger causality, after the econometrician Clive Granger, can be useful when direct interference in the experiment is undesirable or impossible. In epidemiology, for instance, a study of heart disease in a selected population might consider obesity, smoking habits, family history, and other relevant causal factors. A statistical model that involves those factors as variables can provide information on their possible influence.

Output: corroborate


Input: Claim: Biodegradable plastics will completely replace traditional plastics by 2030. [SEP] Text: coli, phb genes, transgenic plant, bacterial fermentation, non-biodegradable, ecosystems Abbreviations PHB, poly-3-hydroxybutyrate; PHAs, polyhydroxyalkanoates; EMP, embden-meyerhof-parnas; PP, pentose phosphate; ED, entner doudoroff; SD, serine deaminase (PHAs) represent a diverse group of polyesters known as bioplastics that are synthesized by many microorganisms as intracellular carbon and energy storage compounds under stress conditions. 1 Since PHAs are completely biodegradable and have thermoplastic or elastomeric properties, they could offer an excellent alternative to non-biodegradable petrochemical based plastics. 2 However, the production cost of biodegradable plastics is comparatively very high that limits its industrial production. As a result, the current world is heavily dependent on non-biodegradable petrochemical plastics that are very cheap. Consequently, millions of tons of non-biodegradable waste plastics are usually burned and/or dumped in landfills worldwide every year, which basically increase carbon footprint in the environment leading to global warming and natural calamities through affecting natural ecosystems. Poly-3-hydroxybutyrate (PHB) is widely studied and best-characterized thermoplastic polyester within PHA family, which can be used to produce a wide range of household and packaging products such as grocery bags, soda bottles, disposable razors, flatware, etc. When they are discarded after use, the soil bacteria degrade the bioplastics naturally into water and carbon dioxide within a very short period of time. In addition, PHB and its derivatives are currently used in the medical procedures such as internal suture, vehicle for drug delivery, etc. Since bioplastics are nontoxic, biodegradable and biocompatible, they do not have to be removed after patient’s recovery. PHB occurs naturally in bacteria such as Ralstonia eutropha and Bacillus megaterium that has become a model polymer for research on PHA, and for establishing and optimizing biotechnological production processes. PHB synthetic pathway genes from Ralstonia eutropha have been expressed in E. coli in order to maximize the PHB production since the bacteria E.

Output: contrast


Input: Claim: Every ancient civilization has left behind detailed written records. [SEP] Text: Did you explore using sexually active 15-19 yrs olds? For the age analysis, the findings are for all women where possible. There is a separate analysis for unmarried sexually active women. The conclusion is a bit difficult to follow. It’s not just about – were there any significant gains in vulnerable populations. What we want to see is that programs focused on these groups and we saw them “catch up”. How did their gains compare with gains elsewhere? Perhaps you could start the conclusion with some general statements about which population groups saw the greatest increases in country (vulnerable or not) and then focus on the countries that show significant gains in reducing inequities. We do start the conclusions with some general statements. Since we cannot measure direct program effect in this paper, we added a point in the discussion where we mention this has a limitation. Overall, we found your feedback to be incredibly helpful. Thank you for taking the time to make comments. Specific questions are addressed below. While MCPR is a useful measure for this exercise, it does not provide the full picture of equity in FP. For example, unmet need for contraception may provide a better measure at how well programs are meeting demand. Likewise, MCPR does not capture client experience or the ability of the system to provide a preferred method. For purposes of this analysis, I agree MCPR works well, however, I suggest the authors acknowledge this limitation. We added additional information on this in the methods section where we discuss why we opted to use MCPR and then also added in the discussion section limitation of how our analysis in unable to provide an analysis on client experience or the ability of the system to provide a woman’s preferred method. The current version is a high quality academic paper. It would be helpful to include some recognition that inequities are a result of the system's inability to serve the needs of particular communities. These differences mark important differences in power structures and resource allocation. We added in a note on how resource allocation and tailored programming towards reducing inequities is likely what allowed countries to grow MCPR. Following the point above, in countries where the equity gaps has shrunk, it would be helpful to acknowledge that this is due to the program's ability to shift these power and resource imbalances. They have been able to reshape programs to reflect the values and p1. This one is easy to read. It would be more interesting to present the diff in diff analysis.

Output: pass


Input: Claim: Climate change is causing an increase in the frequency of extreme weather events. [SEP] Text: For climate, scientists have developed extreme-value statistical models using greenhouse gas concentrations, air pollution, urbanization, El Niño, and other natural modes of variability as covariates to isolate their relative influence on extreme weather. and Granger causal-inference techniques have their strengths and limitations. Granger causal inference may lead to the post hoc, ergo propter hoc fallacy—that correlation does not necessarily imply causality. Additionally, the influence of unspecified covariates must be considered. causal inference relies on models, one must first ascertain whether the model is fit for the purpose at hand. Many extreme weather events are poorly simulated when available public climate model data sets are used, and thus those data sets are unsuitable for attribution studies. Confidence in attribution statements is increased when both Granger and Pearl causal-inference techniques can be invoked and produce similar results. Confidence is further increased when multiple independent research groups use different models, observations, and methods and arrive at similar conclusions. One motivation for performing extreme-event attribution studies is to satisfy the public’s curiosity about how climate change affects them. But an equally important motivation is gaining insight into the physical mechanisms behind the changes in extreme weather events. Borrowing concepts from epidemiology, scientists hope to untangle and quantify the different causal factors. The ongoing work focuses on answering two questions: “Did climate change affect the magnitude of an event of a given estimated rarity? ” and “Did climate change cause the chances of an event of an observed high magnitude to change? ” Extreme heat Those two questions are two sides of the same coin, as illustrated by the abnormally hot temperatures in Texas during the summer of 2011. Figure 1a shows observed Texas summer temperature departures (purple) from the average of the 1961–90 temperatures. Two simulations are shown, one with realistic human changes to the atmospheric composition (orange)—mainly well-mixed greenhouse gas increases, stratospheric ozone decreases, and aerosol pollution—and the other counterfactual (green), in which temperatures are cooler because it doesn’t include the effect of human changes. Both the observations and the predicted data in the realistic model trend upward. The absence of such a trend in the counterfactual simulation reveals that there is an attributable human influence on Texas summer temperatures. Increasingly hot summers are expected. Yet the 2011 temperature, shown by the black dot, was about 2.

Output: corroborate


Input: Claim: Biodegradable plastics will completely replace traditional plastics by 2030. [SEP] Text: Until today, no single strategy has been shown to be effective for the production of bioplastics in order to compete with petroleum-based plastics. Therefore, the advanced and integrated approaches must be considered for production of biodegradable plastics. One such strategy would be to explore an integrated waste water treatment plant where different types of native and/or recombinant microorganism including E. coli, microalgae and diatom will be harvested in sequential procedures or in mixed cultures for concomitant production of bioplastics and biofuel besides clean water (Figure 2). Figure 2 An advanced and integrated waste water treatment plant to produce PHB. Acknowledgements None. Conflict of interest The author declares no conflict of interest. 774. Choi J, Lee SY. Efficient and economical recovery of poly (3-hydroxybutyrate) from recombinant Escherichia coliby simple digestion with chemicals. Biotechnol Bioeng. 1999;62(5):546–553. Kabir MM, Shimizu K. Fermentation characteristics and protein expression patterns in a recombinant Escherichia colimutant lacking phosphoglucose isomerase for poly (3-hydroxybutyrate) production. Biotechnol. 2003;62(2-3):244–255. Kabir MM, Shimizu K. Proteome analysis of a temperature-inducible recombinant Escherichia colifor poly-hydroxybutyrate production. J Biosci Bioeng. 2001;92(3):277–284. Engineering of erinedeamination pathway, Entner-Doudoroff pathway and pyruvate dehydrogenase complex to improve poly (3-hydroxybutyrate) production in Escherichia coli. Factories. 2014;13:172. . High-level production of poly (3-hydroxybutyrate-co-3- hydroxyvalerate) by fed-batch culture of recombinant Escherichia coli. Microbiol. 1999;65(10):4363–4368. Metabolic engineering of Escherichia colifor enhanced biosynthesis of poly (3- hydroxybutyrate) based on proteome analysis. Biotechnol Lett. 2013;35(10):1631–1637. .

Output: contrast


Input: Claim: Every ancient civilization has left behind detailed written records. [SEP] Text: All countries in the wealth graphic should have two bubbles. One bubble is for the earlier survey and the second bubble is for the later survey. We opted not to do a regression analysis (which would be a difference in difference analysis) and our reasoning added to the discussion section. We will add additional notes that will help with the interpretation. I appreciate the reference and cut off according to confidence interval, but is there a way to include them in the paper? The confidence intervals are included in the paper. For interpretability of the findings, we opted to keep them in tables and not directly in text. I don’t believe it is appropriate to compare the most vulnerable (poorest) with the most advantaged (wealthiest). I recommend focusing your analysis on comparing the most vulnerable to an index population (poorest with middle income), as you have done and drop the other analysis. This comparison is more appropriate in my view and could make the figures and analysis easier to communicate. This is true for education and age as well. We wanted to compare the most disadvantaged group to the least disadvantaged group because we wanted to assess if the most vulnerable (disadvantaged) were left behind while the most advantaged continued to progress. While we focus on these two groups in most of the analysis, we do calculate MCPR among all levels of the equity dimensions and those comparisons can be made by all readers by reviewing the tables. The residential analysis doesn’t reflect on shifts in demographics. Was there a significant shift in people from rural to urban settings? We investigated this question, and we did not see any change in people moving from rural to urban settings in every country between surveys. I can’t follow the finding on age. Please clarify. Did you limit the analysis to married women 15-19? Did you explore using sexually active 15-19 yrs olds? For the age analysis, the findings are for all women where possible. There is a separate analysis for unmarried sexually active women. The conclusion is a bit difficult to follow. It’s not just about – were there any significant gains in vulnerable populations. What we want to see is that programs focused on these groups and we saw them “catch up”. How did their gains compare with gains elsewhere? Perhaps you could start the conclusion with some general statements about which population groups saw the greatest increases in country (vulnerable or not) and then focus on the countries that show significant gains in reducing inequities.

Output: pass


Input: Claim: Climate change is causing an increase in the frequency of extreme weather events. [SEP] Text: 5 °C warmer than the average summer and was considered a rare, 1-in-30-year event at the time. Figure 1. View largeDownload slideDeparture from average summer temperatures in Texas. (a) A realistic historical simulation (orange) and a cooler counterfactual climate without anthropogenic climate change (green) are compared with the observations (purple). The black dot represents the observed value of 2. 467 °C for 2011. The solid lines represent the smoothed temperature anomalies. (Adapted from ref. 6. ) (b) Simulations show the likelihood of Texas summer surface air temperature in a realistic climate (orange) and the cooler counterfactual climate (green). A return value (maximum temperature) has a 1/(return time) chance of being met or exceeded in a given year. The dashed line indicates that the observed temperature was a 1-in-30-year event in 2011, and it was 1. 5 °C warmer than it would’ve been without climate change. Figure 1. View largeDownload slideDeparture from average summer temperatures in Texas. (a) A realistic historical simulation (orange) and a cooler counterfactual climate without anthropogenic climate change (green) are compared with the observations (purple). The black dot represents the observed value of 2. 467 °C for 2011. The solid lines represent the smoothed temperature anomalies. (Adapted from ref. 6. ) (b) Simulations show the likelihood of Texas summer surface air temperature in a realistic climate (orange) and the cooler counterfactual climate (green). A return value (maximum temperature) has a 1/(return time) chance of being met or exceeded in a given year. The dashed line indicates that the observed temperature was a 1-in-30-year event in 2011, and it was 1. 5 °C warmer than it would’ve been without climate change. Close modal To answer the two event-attribution questions about changes in event magnitude and frequency, one needs to turn to the climate-model data. Figure 1b shows the return values of average summer temperatures in Texas as a function of time. The return value is the highest average temperature expected to be reached once in a given period of time, known as the return time. The solid orange line, representing the realistic simulation, reveals that an average temperature of 34 °C would occur once in 30 years.

Output: corroborate


Input: Claim: All biodegradable plastics are safe for marine life and will not harm ocean ecosystems. [SEP] Text: Policy: ASTM International prohibits the entry of ASTM standards and related ASTM intellectual property (“”) into any form of (AI) tools, such as ChatGPT. Additionally, creating ----derivatives of using AI is also prohibited without express written permission from ASTM’s President. In the case of such use, ASTM will suspend a licensee’s access to and further legal action will be considered. Meetings & | Meetings & & & Standards and Papers & STPs Manuals, Monographs, & of ® (SOP) (TMA) and & & & & and ASTM What is and to to News and & -08. 03 Committee D20 $ 0. 00 Out of stock AbstractThis specification covers non-floating products made from plastics (including packaging and coatings) that are designed to be biodegradable under the marine environmental conditions of aerobic marine waters or anaerobic marine sediments, or both. (Possible environments are shallow and deep salt water and brackish water. ) This specification is intended to establish the requirements for labeling materials and products, including packaging, as "biodegradable in marine waters and sediments. " The products should exhibit satisfactory performances in terms of disintegration during marine degradation, inherent biodegradation, and environmental toxicity. However, this specification does not describe the contents or their performance with regard to biodegradability. Scope1. 1 This specification covers products made from plastics (including packaging and coatings) that are designed to be biodegradable under the marine environmental conditions of aerobic marine waters or anaerobic marine sediments, or both. (Possible environments are shallow and deep salt water and brackish water. )1. 2 This specification is intended to establish the requirements for labeling materials and products, including packaging, as "biodegradable in marine waters and sediments. "1. 3 The properties in this specification are those required to determine if products (including packaging) will biodegrade satisfactorily, including biodegrading at a rate comparable to known compostable materials. Further, the properties in the specification are required to assure that the degradation of these materials will not diminish the value or utility of the marine resources and habitat. 1. 4 This specification does not describe contents or their performance with regard to biodegradability. 1.

Output: contrast


Input: Claim: Every ancient civilization has left behind detailed written records. [SEP] Text: We do start the conclusions with some general statements. Since we cannot measure direct program effect in this paper, we added a point in the discussion where we mention this has a limitation. Competing Interests: No competing interests were disclosed. a concern Respond or 28 Jan 2022 Shiza Shiza, FP2020, Washington, 20006, USA 28 Jan 2022 Overall, we found your feedback to be incredibly helpful. Thank you for taking the time to make comments. Specific questions are addressed below. While MCPR is a useful. . . Continue reading Overall, we found your feedback to be incredibly helpful. Thank you for taking the time to make comments. Specific questions are addressed below. While MCPR is a useful measure for this exercise, it does not provide the full picture of equity in FP. For example, unmet need for contraception may provide a better measure at how well programs are meeting demand. Likewise, MCPR does not capture client experience or the ability of the system to provide a preferred method. For purposes of this analysis, I agree MCPR works well, however, I suggest the authors acknowledge this limitation. We added additional information on this in the methods section where we discuss why we opted to use MCPR and then also added in the discussion section limitation of how our analysis in unable to provide an analysis on client experience or the ability of the system to provide a woman’s preferred method. The current version is a high quality academic paper. It would be helpful to include some recognition that inequities are a result of the system's inability to serve the needs of particular communities. These differences mark important differences in power structures and resource allocation. We added in a note on how resource allocation and tailored programming towards reducing inequities is likely what allowed countries to grow MCPR. Following the point above, in countries where the equity gaps has shrunk, it would be helpful to acknowledge that this is due to the program's ability to shift these power and resource imbalances. They have been able to reshape programs to reflect the values and p1. This one is easy to read. It would be more interesting to present the diff in diff analysis. All countries in the wealth graphic should have two bubbles. One bubble is for the earlier survey and the second bubble is for the later survey. We opted not to do a regression analysis (which would be a difference in difference analysis) and our reasoning added to the discussion section. We will add additional notes that will help with the interpretation.

Output: pass


Input: Claim: Climate change is causing an increase in the frequency of extreme weather events. [SEP] Text: In the counterfactual simulation, shown by the green line, the average temperature occurring once every 30 years would be just over 32 °C. Thus the answer to the first question is that climate change increased the average temperature of a 1-in-30-year event by about 2 °C. To answer the second question about the change in rarity, one needs to estimate chances of an average temperature of 34. 2 °C without any climate change. The observed temperature is near the upper bound of the counterfactual distribution, and the return time is estimated to be 66 million years. Publishing an attribution statement based on that estimate would be unwise, however, because the uncertainties from extrapolating out that far are extreme. Best practice is to put uncertainty bounds on the ratio of those return times. Using a likelihood ratio test, scientists can place a 95% confidence interval of 16 to infinity on the ratio of counterfactual to observed return times. In plain language, climate change increased the chances of the observed 2011 Texas summer temperature by at least a factor of 16. The current global warming level of about 1. 2 °C above preindustrial levels means that any rare heat wave that now occurs has an attributable human influence (reference 3, 34. 2 °C in Texas—is more uncertain because of both the statistical model and event characterization, although the lower bound on probability changes has been found to be independent of estimates of event magnitude. 7,8 the human influence on heavy precipitation events is more complicated than for heat waves for several reasons. The first is that precipitation is a sporadic event, and extreme precipitation even more so. (To learn about human influences on monsoons, see page 32 in this issue. ) Well-established theory (the Clausius–Clapeyron relation) and traditional trend analysis reveal that saturation specific humidity increases by about 7% per 1 °C of local warming. Because extreme precipitation usually occurs in fully saturated atmospheric conditions, one might expect the likelihood of such an event to also increase at the same rate. The more likely a local area is to be fully saturated, the more likely it is to rain. Analyses that used the 100 km climate models on extreme precipitation trends confirm that rate of increase (reference 3, 2017. 8,11,12 A best estimate distilled from those papers is that climate change increased Harvey’s rainfall by 19%, or about 2.

Output: corroborate


Input: Claim: All biodegradable plastics are safe for marine life and will not harm ocean ecosystems. [SEP] Text: 4A, if the authors would refer them to the respective literature in (eco)toxicology. The model seems to be based on a single example, abnormality of Mytilus edulis. It is questionable that there is a linear relationship between chemical and biological change in all species and in all indicators. I suggest to use the large amount of laboratory results (OA-ICC at the database pangaea. de) and a variety of indicators to develop a more robust model. The conclusion that insensitive systems require longer monitoring is trivial from the viewpoint of an experimental biologist as this must be considered when planning experiments and when interpreting results. While clearly illustrated in this manuscript, I doubt that this is new information to researchers involved in monitoring programs. An innovative approach would allow to consider processes such as transgenerational effects of OA (see e. g. Parker et al. 2015) and multiple drivers of biological change. I suggest to include a figure that at least conceptually depicts how dose-response curves may be affected. Specific comments L 63-66: This sentence suggests that there are few field (monitoring? ) studies on OA effects outside areas of unusually high CO2 levels. If this is so, I suggest to cite them and briefly summarize the state of the art here or in the following paragraph. This would give the reader a brief overview of what could be intensified/improved in the future. Otherwise, consider rephrasing this sentence and the sentence in l 462-464 of the conclusions. Also good to know here: Are there any monitoring data that allow the analysis of biological OA effects, and this just has not been done yet? L 75 ff Introduction: More explicitly name and address here and in the conclusions. Clearly point out and explain the contribution of ecophysiology/experimental studies to improving the framework with respect to OA here and in the conclusions (e. g. Hayes et al. 2015, Kissling et al. 2018, Pereira et al. 2013). I. e. what are the gaps this paper fills? L 132: Replace “or” with “and”. Physiological data are important to attribute impacts to any environmental driver. Ecological data alone do not allow this. And vice versa. L 137 ff: State how these ecosystem traits and indicators relate to EOVs and EBVs (see 2013. L 410: Why was linear regression used?

Output: contrast


Input: Claim: Every ancient civilization has left behind detailed written records. [SEP] Text: I appreciate the reference and cut off according to confidence interval, but is there a way to include them in the paper? The confidence intervals are included in the paper. For interpretability of the findings, we opted to keep them in tables and not directly in text. I don’t believe it is appropriate to compare the most vulnerable (poorest) with the most advantaged (wealthiest). I recommend focusing your analysis on comparing the most vulnerable to an index population (poorest with middle income), as you have done and drop the other analysis. This comparison is more appropriate in my view and could make the figures and analysis easier to communicate. This is true for education and age as well. We wanted to compare the most disadvantaged group to the least disadvantaged group because we wanted to assess if the most vulnerable (disadvantaged) were left behind while the most advantaged continued to progress. While we focus on these two groups in most of the analysis, we do calculate MCPR among all levels of the equity dimensions and those comparisons can be made by all readers by reviewing the tables. The residential analysis doesn’t reflect on shifts in demographics. Was there a significant shift in people from rural to urban settings? We investigated this question, and we did not see any change in people moving from rural to urban settings in every country between surveys. I can’t follow the finding on age. Please clarify. Did you limit the analysis to married women 15-19? Did you explore using sexually active 15-19 yrs olds? For the age analysis, the findings are for all women where possible. There is a separate analysis for unmarried sexually active women. The conclusion is a bit difficult to follow. It’s not just about – were there any significant gains in vulnerable populations. What we want to see is that programs focused on these groups and we saw them “catch up”. How did their gains compare with gains elsewhere? Perhaps you could start the conclusion with some general statements about which population groups saw the greatest increases in country (vulnerable or not) and then focus on the countries that show significant gains in reducing inequities. We do start the conclusions with some general statements. Since we cannot measure direct program effect in this paper, we added a point in the discussion where we mention this has a limitation. Overall, we found your feedback to be incredibly helpful. Thank you for taking the time to make comments. Specific questions are addressed below.

Output: pass


Input: Claim: Climate change is causing an increase in the frequency of extreme weather events. [SEP] Text: 5 times as much as what might be expected from Clausius–Clapeyron scaling of the increased available moisture from the 1 °C of attributable warming in the Gulf of Mexico. Since Harvey, numerous other tropical storms have been analyzed and have revealed similar scaling of precipitation statistics. 10,13 The mechanism for the super Clausius–Clapeyron scaling is simple. Figure 2a shows the composite simulated precipitation from Hurricane Maria, which devastated in 2017. Figure 2b shows the attributable precipitation changes at the time it occurred, and figure 2c shows the hypothetical precipitation changes in a much warmer world. The first thing to notice is that the increases, either in an absolute or relative sense, are the largest in the rainiest parts of the storm. The second is that there are decreases in the outer precipitation bands. What is happening is that warmer conditions are likely increasing the storm’s wind speeds. While the changes in instantaneous maximum wind speeds are thought to be slight at present, they will become more robust in a much warmer world. That increase in tropical cyclone intensity causes the storm structure to change and become more efficient at precipitating available moisture. Figure 2. View largeDownload slideChanges in precipitation during in 2017 relative to the cyclone center throughout its lifetime. (a) Composite simulated precipitation across multiple simulations under realistic climate conditions. (b) Attributable change in precipitation calculated from realistic simulations and a cooler, counterfactual simulation approximating preindustrial conditions. (c) Projected change in precipitation calculated from realistic simulations and counterfactual conditions at 3. 5 °C warmer than preindustrial conditions, or how much worse it could’ve been. Contours indicate the rainfall rate from the historical simulation. The plots are in units of the grid resolution, 4. 5 km. (Adapted from ref. 13. )Figure 2. View largeDownload slideChanges in precipitation during in 2017 relative to the cyclone center throughout its lifetime. (a) Composite simulated precipitation across multiple simulations under realistic climate conditions. (b) Attributable change in precipitation calculated from realistic simulations and a cooler, counterfactual simulation approximating preindustrial conditions. (c) Projected change in precipitation calculated from realistic simulations and counterfactual conditions at 3. 5 °C warmer than preindustrial conditions, or how much worse it could’ve been. Contours indicate the rainfall rate from the historical simulation. The plots are in units of the grid resolution, 4. 5 km.

Output: corroborate


Input: Claim: All biodegradable plastics are safe for marine life and will not harm ocean ecosystems. [SEP] Text: Drawn from toxicological concepts? If so, please cite respective literature. L 411-412: Please provide evidence that supports this general statement. L 785: Figure 4: Add pH scales to the x-axis to clarify that these are dose-response curves. Technical corrections L 51: Delete “process”. L 63-66: Long sentence, consider revising. L 66: Provide full citation for OA-ICC. L 73: Sentence “Biological observations…”: Replace “it” with “they”. L 141: Add “should be” in front of “associated”. L193: Delete “might”. L 326: Insert “GenBank and the Archive (ENA)” after “(NCBI)”. L 337: Replace “environmentally” with “environmental”; add “as” after “such”. L 340: Delete comma. 10. 1016/j. ecolind. 2015. 05. 006 Kissling, W. D. , Walls, R. , Bowser, A. et al. Towards global data products of Variables on species traits. Evol 2, 1531–1540 (2018). Parker LM, O'örtner HO, Ross PM. Persistence of Effects in the Oyster, Saccostrea glomerata, following to Ocean Acidification. PLoS One. 2015 Jul 6;10(7):e0132276. doi: 10. 1371/journal. pone. 0132276. Pereira et al. 2013 Variables - A global system of harmonized observations is needed to inform scientists and policy-makers DOI: 10. 1126/science. 1229931 Citation: AC2: 'Reply on RC2', Sam Dupont, 15 Dec 2022 #2We would like to thank the reviewer for these valuable and constructive comments and suggestions. See below for our detailed responses. Reviewer comment: It is timely that indicators are defined that help to attribute biological change to OA. This manuscript shows how experimental studies can inform monitoring strategies. The authors claim that there is a linear relationship between the rates of chemical and biological change. They claim that this concept could bring together a variety of indicators from different sites to attribute change to OA.

Output: contrast


Input: Claim: Every ancient civilization has left behind detailed written records. [SEP] Text: While MCPR is a useful measure for this exercise, it does not provide the full picture of equity in FP. For example, unmet need for contraception may provide a better measure at how well programs are meeting demand. Likewise, MCPR does not capture client experience or the ability of the system to provide a preferred method. For purposes of this analysis, I agree MCPR works well, however, I suggest the authors acknowledge this limitation. We added additional information on this in the methods section where we discuss why we opted to use MCPR and then also added in the discussion section limitation of how our analysis in unable to provide an analysis on client experience or the ability of the system to provide a woman’s preferred method. The current version is a high quality academic paper. It would be helpful to include some recognition that inequities are a result of the system's inability to serve the needs of particular communities. These differences mark important differences in power structures and resource allocation. We added in a note on how resource allocation and tailored programming towards reducing inequities is likely what allowed countries to grow MCPR. Following the point above, in countries where the equity gaps has shrunk, it would be helpful to acknowledge that this is due to the program's ability to shift these power and resource imbalances. They have been able to reshape programs to reflect the values and p1. This one is easy to read. It would be more interesting to present the diff in diff analysis. All countries in the wealth graphic should have two bubbles. One bubble is for the earlier survey and the second bubble is for the later survey. We opted not to do a regression analysis (which would be a difference in difference analysis) and our reasoning added to the discussion section. We will add additional notes that will help with the interpretation. I appreciate the reference and cut off according to confidence interval, but is there a way to include them in the paper? The confidence intervals are included in the paper. For interpretability of the findings, we opted to keep them in tables and not directly in text. I don’t believe it is appropriate to compare the most vulnerable (poorest) with the most advantaged (wealthiest). I recommend focusing your analysis on comparing the most vulnerable to an index population (poorest with middle income), as you have done and drop the other analysis. This comparison is more appropriate in my view and could make the figures and analysis easier to communicate.

Output: pass


Input: Claim: Climate change is causing an increase in the frequency of extreme weather events. [SEP] Text: (Adapted from ref. 13. ) Close modal Hurricanes receive much of the attention in the attribution community, but other storm types are worth studying. A recent storyline analysis found that precipitation from a selected group of strong atmospheric-river storms affecting the coincidentally also increased at about twice the Clausius–Clapeyron rate. 9 Analysis suggests that those physical mechanisms of change are very different than inferred for tropical cyclones. Although few additional studies have been made of atmospheric rivers that impact coastal zones, the information has been alarming enough for decision makers to act on it. Although interest is high, little is known with confidence about anthropogenic increases in the intense summer mesoscale convective systems that can occur in continental interiors, partly because of computational constraints. Limited studies have analyzed the human influence on environmental conditions that support tornadoes, but there is no consensus regarding how climate change has influenced tornados. 14 the impact of climate change on drought can be complicated. One must consider the different types of droughts. NOAA classifies drought as a hierarchy of four related conditions. Meteorological drought is characterized by a deficit of precipitation; agricultural or ecological drought, of soil moisture; and hydrological drought, of water supply. Socioeconomic drought occurs when demand for water exceeds the supply. Agricultural drought depends on both the precipitation that falls on the ground and the evapotranspiration of moisture from plants and soils. Evaporation from bare ground depends strongly on air temperature. As the temperature increases from climate change, evaporation increases lead to drier soils. Transpiration from plants depends even more strongly on air temperature. Plants cool themselves by opening their stomata and evaporating water. In hot conditions, they can draw moisture from their root system until little soil moisture is left. Decreased soil moisture may in turn limit evapotranspiration, which means the relationship between temperature and soil moisture isn’t linear. Recent literature shows that human-induced climate change has contributed to increases in agricultural droughts in some regions because of evapotranspiration increases (reference 3, 2017. A counterfactual “flood that might have been” was constructed by decreasing Harvey’s observed precipitation uniformly according to published precipitation-attribution statements and using that as the input to a credible flood model.

Output: corroborate


Input: Claim: All biodegradable plastics are safe for marine life and will not harm ocean ecosystems. [SEP] Text: While the identified indicators can develop the EOV/EBV framework further, I find the correlation/linear regression of chemical and biological rates of change questionable. Author response: We thank the reviewer for the comments and for highlighting an area of the manuscript where we haven’t communicated the details of our approach as clearly as we should have. The underlying purpose of this paper is to introduce the concept that, if ocean acidification is the main (or strongly contributing) driver of change for a given ecosystem or biological parameter, it should be possible to describe a statistical relationship between the rate at which the carbonate chemistry is changing and the rate at which the observed biological parameter is changing. For simplicity, we chose to illustrate this point using a linear relationship (Figure 2) but we fully acknowledge that this relationship could follow one of many different models. Linear regression can be a good alternative and the null model used to test the data, so at least everyone involved in this approach will have the same starting point (the null model) although the ending point could be context-specific (depending on sensitivities, local changes, etc. ) In fact, situations where the relationship model deviates from a simple linear one will allow us to explore the key modulating roles of other drivers and/or ecological interactions that may also be influencing the rate of biological change. We have now added text into the manuscript to clarify this point. Added text: “While we use a linear relationship between the chemical and biological rates of change as an illustration in the Fig. 2, the precise nature of this relationship is currently unknown and may follow other pattern such as a non-linear tipping point responses (e. g. Wunderlink et al. , 2021). We also welcome the reviewer’s reminder of the importance of developing indicators. such as those we propose, to develop the EOV/EBV framework further. We have added text to the introduction to better describe this and added a reference. Added text: “If widely adopted, the approaches proposed in this paper would promote much greater co-location of biological and ocean acidification monitoring to help better understand the biological consequences of ocean acidification in the real world. This outcome aligns with previous recommendations (Muller-Karger et al. , 2018b) which call for greater global connectivity between the collection of Variables (EOVs) through the (GOOS), and Variables (EBVs) from the Group on Network ().

Output: pass


Input: Claim: Every ancient civilization has left behind detailed written records. [SEP] Text: This is true for education and age as well. We wanted to compare the most disadvantaged group to the least disadvantaged group because we wanted to assess if the most vulnerable (disadvantaged) were left behind while the most advantaged continued to progress. While we focus on these two groups in most of the analysis, we do calculate MCPR among all levels of the equity dimensions and those comparisons can be made by all readers by reviewing the tables. The residential analysis doesn’t reflect on shifts in demographics. Was there a significant shift in people from rural to urban settings? We investigated this question, and we did not see any change in people moving from rural to urban settings in every country between surveys. I can’t follow the finding on age. Please clarify. Did you limit the analysis to married women 15-19? Did you explore using sexually active 15-19 yrs olds? For the age analysis, the findings are for all women where possible. There is a separate analysis for unmarried sexually active women. The conclusion is a bit difficult to follow. It’s not just about – were there any significant gains in vulnerable populations. What we want to see is that programs focused on these groups and we saw them “catch up”. How did their gains compare with gains elsewhere? Perhaps you could start the conclusion with some general statements about which population groups saw the greatest increases in country (vulnerable or not) and then focus on the countries that show significant gains in reducing inequities. We do start the conclusions with some general statements. Since we cannot measure direct program effect in this paper, we added a point in the discussion where we mention this has a limitation. Competing Interests: No competing interests were disclosed. a concern on this 1. While the authors do cite relevant literature, I think reference to the Choi and Fabic 2. Regarding wealth categories, I was not clear on whether these quintiles were defined cross-country or within country. For example, if women were in the poorest households, were these the poorest within their own country or the poorest across all countries? I assume the latter but a slight clarification would make this more clear. 2. Figure 1 - Rather than have two colors differentiating older/later surveys could authors differentiate each country with color/symbol combinations? I think this would make interpretation easier and faster. 3. Figure 2- I applaud the authors creativity in finding a way to visualize quite a bit of information.

Output: pass


Input: Claim: Climate change is causing an increase in the frequency of extreme weather events. [SEP] Text: 15 Figure 3 compares the actual flood depth and the best estimate of the counterfactual one in two Houston neighborhoods, where almost 9 000 homes were flooded. The 19% precipitation increase attributable to human-influenced climate change translated to an additional 1 m of flood waters and a 14% increase in flood area. Equivalently, as a best estimate, the probability of a $90 billion hurricane loss (the amount of estimated insured losses) in Texas was quadrupled because of climate change. Figure 3. View largeDownload slideActual and counterfactual flood simulations in Texas’s and Pasadena neighborhoods during Hurricane Harvey. (a) The flood that was. (Adapted from ref. 15. ) (b) The flood that might have been in the absence of anthropogenic climate change. The difference between the models is the assumption that human activities increased Harvey storm total precipitation by 19%. Colors denote the depth of flood water in meters. Figure 3. View largeDownload slideActual and counterfactual flood simulations in Texas’s and Pasadena neighborhoods during Hurricane Harvey. (a) The flood that was. (Adapted from ref. 15. ) (b) The flood that might have been in the absence of anthropogenic climate change. The difference between the models is the assumption that human activities increased Harvey storm total precipitation by 19%. Colors denote the depth of flood water in meters. Close modal flood model has a resolution of 30 m—about the size of a suburban property—and its results have been made publicly available at The maps permit individuals to understand whether their home would have flooded without human-influenced climate change. Individuals can select different estimates of the human influence on precipitation and locate their home on both the realistic and counterfactual flood maps. That level of detail also permits a more refined damage estimate by combining it with socioeconomic data sets. Projecting real-estate maps onto the flood maps results in a best estimate that approximately 32% of flooded homes in Harris County, where Houston is located, would not have been flooded without climate change. Furthermore, in the actual flood, 75% of the county’s flooded homes were outside the federal 100-year flood plain—likely uninsured against flood damage—adding to the $90 billion insured loss. 16 Figure 4 shows an upper bound on the distribution of homes that were flooded in because of climate change. Figure 4. View largeDownload slideAdditional anthropogenic flooding.

Output: corroborate


Input: Claim: All biodegradable plastics are safe for marine life and will not harm ocean ecosystems. [SEP] Text: Added text: “Ideally, the rate of biological change should be calculated using a non-linear model following the shape of the non-linear performance curve between pH and the tested parameter (e. g. Fig. 3b for % of abnormality). These performance curves can take many forms depending on the measured parameter and species. For example, common shapes of physiological performance curves include U-shape, sigmoidal, logarithmic, exponential, and inverted U-shape (Little & Seebacher, 2021). However, in practice the shape of these curves is often unknown and it would not be possible to derive relevant rates of change from biological observations over relatively short period of time. Under these circumstances, using a linear regression is good alternative. “ Reviewer comment: The model seems to be based on a single example, abnormality of Mytilus edulis. It is questionable that there is a linear relationship between chemical and biological change in all species and in all indicators. I suggest to use the large amount of laboratory results (OA-ICC at the database pangaea. de) and a variety of indicators to develop a more robust model. Author response: The reviewer is quite correct, and the example projections made in this manuscript are based on a non-linear dose response (from Ventura et al. 2016). We then illustrate what the output would be using linear regression (and the associated errors). While we agree that using this approach with other species or even higher taxonomic groups (using synthesis and meta-analysis) is an extremely valuable thing to do we would see this as the natural next step, following on from this current manuscript. As such we consider this new body of work to be beyond the scope of this current manuscript that focusses primarily on presenting a methodology that can be applied by others to do exactly the kind of activity proposed by the reviewer. Reviewer comment: The conclusion that insensitive systems require longer monitoring is trivial from the viewpoint of an experimental biologist as this must be considered when planning experiments and when interpreting results. While clearly illustrated in this manuscript, I doubt that this is new information to researchers involved in monitoring programs. Author response: The reviewer makes a fair point about researchers already involved in biological monitoring, we would respectfully argue that this paper is not solely being directed towards that existing community.

Output: pass


Input: Claim: Every ancient civilization has left behind detailed written records. [SEP] Text: On the whole I like the chart, but did find some sections where I could not find countries across time. For example Nepal/older in panel 3. older is the turquoise dot near Malawi, what is the purple dot? Would the addition of shapes help? Defer to the authors but think a critical review is necessary to make sure the changes in all countries can be easily located in each panel. 4. Very minor change - suggest rewording "Increases were significant in seven countries– Burundi, Ethiopia, and Uganda in rural settings" to "Increases in rural settings were significant in seven countries– Burundi, Ethiopia, and Uganda" 5. Is it possible to show change in education status, similar to what you did for wealth, to demonstrate both how mcp use has changed and how education status has changed? Fine if not, but it seems like it would compliment the wealth analysis. Is the work clearly and accurately presented and does it cite the current literature? the study design appropriate and is the work technically sound? sufficient details of methods and analysis provided to allow replication by others? applicable, is the statistical analysis and its interpretation appropriate? all the source data underlying the results available to ensure full reproducibility? the conclusions drawn adequately supported by the results? Yes 1. Choi Y, M: in Equality for the Goals: A of for Family Planning. Sci Pract. 2018; 6 (2): 390-401 Pub| competing interests were disclosed. Family planning, demography, survey analysis I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard, however I have significant reservations, as outlined above. replyRespond to this report Responses (0) keyboard_arrow_left Back to all reports 0 Views copyright © 2022 Malarcher S. This is an open access peer review report distributed under the terms of the Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. 08 Feb 2022 | for Version 2 Shawn Malarcher, Agency for 0 Views copyright © 2022 Malarcher S. This is an open access peer review report distributed under the terms of the Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Output: pass


Input: Claim: Climate change is causing an increase in the frequency of extreme weather events. [SEP] Text: Each hexagonal bin symbolizes the upper limit of the number of residential buildings that would not have flooded without the added impact of climate change in Harris County, Texas, during in 2017. (Adapted from ref. 16. )Figure 4. View largeDownload slideAdditional anthropogenic flooding. Each hexagonal bin symbolizes the upper limit of the number of residential buildings that would not have flooded without the added impact of climate change in Harris County, Texas, during in 2017. (Adapted from ref. 16. ) Close modal Census data further reveal that Hurricane Harvey’s flood damages were not equally distributed across socioeconomic groups. Hispanic households are about 36% of the population of Harris County, but they owned or rented roughly 50% of the flooded homes. Additional analysis reveals that in wealthy neighborhoods, damages increased for households with more wealth. In low-income neighborhoods, the opposite trend was found: that damages increased for households with less wealth. Given the relative contribution to increases in greenhouse gases from people who are wealthy compared with people who are economically marginalized, such analyses quantify environmental and other social injustices. 16 More than just a weather forecast Other human impacts of extreme weather can also be quantified. Of particular interest is whether climate change increases the number of deaths from heat waves. They are among the deadliest of all extreme weather events, and epidemiology studies have developed relationships between mortality risk and temperature. 17 At high temperatures, the relationship becomes more sensitive: In already hot weather, a small increase in temperature can cause large increases in mortality. Scientists can use the relationship when estimating the attributable human temperature increase to understand the change in mortality risk during a heat wave. Another method maps mortality and temperature curves onto temperature-change plots, like those in figure 1, to estimate the number of people who have died because of the influence of climate change on a heat wave and to determine how the probability of death has changed. 18 The models are not perfect. Incorporating adaptive measures—for example, cooling centers and other outreach that can reduce the heat wave mortality risk—into attribution statements is currently challenging. There are many additional factors to consider when extending attribution statements about the human influence on extreme weather events to attribution statements about the human influence on the events’ outcomes. The sixth assessment report of the on declares that “human-induced climate change is already affecting many weather and climate extremes in every region across the globe” (reference 3, page 8).

Output: corroborate


Input: Claim: All biodegradable plastics are safe for marine life and will not harm ocean ecosystems. [SEP] Text: While clearly illustrated in this manuscript, I doubt that this is new information to researchers involved in monitoring programs. Author response: The reviewer makes a fair point about researchers already involved in biological monitoring, we would respectfully argue that this paper is not solely being directed towards that existing community. Coupled ocean acidification and biological impact observation/monitoring is largely absent in many countries and we feel it is useful to clarify even some of the most fundamental principles for other audiences, to promote a greater awareness and engagement in other stakeholders who we would hope to encourage to implement greater biological monitoring, complemented with carbonate chemistry measurements. Many of these stakeholders are non-biologist academics, environmental managers, funders of monitoring programmes and marine industry partners. We should also not forget that for a truly global picture to emerge we also need to make this manuscript accessible to those researchers looking to develop capacity and capability in countries with little or no experience in this type of monitoring. Consequently, we would prefer to keep this part of the conclusion, even if it may seem somewhat basic for some readers. Reviewer comment: An innovative approach would allow to consider processes such as transgenerational effects of OA (see e. g. Parker et al. 2015) and multiple drivers of biological change. I suggest to include a figure that at least conceptually depicts how dose-response curves may be affected. Author response: The reviewer makes a good point. We did think that we had implicitly covered the potential modulating role of transgenerational acclimation, evolution or other drivers in leading to change in species sensitivity this in Figure 6. To make this point more clearly we have modified the text. Modified text: “It is also important to note that other parameters/stressors, short term variability, ecology and evolution can modulate the biological response and then influence the rate of biological change. As an example, we compared rates of biological changes in 3 ‘hypothetical model’ organisms with different levels of sensitivity to pH (Fig. 3b). This scenario could represent different populations of the same species adapted to different levels of pH variability (e. g. Vargas et al. , 2017, 2022) or with different modulating factors (e. g. temperature or food concentration) or evolution of the performance curve within one population through time as a consequence of transgenerational adaptation or evolution (Parker et al.

Output: contrast


Input: Claim: Every ancient civilization has left behind detailed written records. [SEP] Text: format_quote Cite this report speaker_notes Responses(0) Approved info_outline Alongside their report, reviewers assign a status to the 2020. The selective citing of policies related to increases in MCP among certain groups (e. g. , Malawi’s focus on youth) distracts from the overall finding/message (that FP2020 commitments, as they were applied within countries, did not seem to exacerbate inequalities writ large). These policies are also cited inconsistently – e. g. , credited for MCP gains among Malawi youth but no such policy is cited for the substantial gains among Malawi’s uneducated women – and thus come across as selective. I generally found the graphics challenging to read and interpret, with the key messages not clearly represented visually. Perhaps fewer and simpler graphics could better convey the main findings. I’d like more discussion about implications of the findings that some advantaged groups have experienced MCP stagnation or declines. Does this imply an inequitable focus on these groups, suggesting further declines among these groups under the FP2020 “equity” approach? Unlikely, but this could still have implications about how the FP2030 defines equity moving forward. After reinforcing their message that in its aim of reaching 120 million additional users FP2020 does not seem to have widened the use gap between advantaged and disadvantaged women, I’d encourage the authors to give a bit more consideration to their findings on MCP declines among several more advantaged groups and the implications this might have for FP2030. Is the work clearly and accurately presented and does it cite the current literature? the study design appropriate and is the work technically sound? sufficient details of methods and analysis provided to allow replication by others? applicable, is the statistical analysis and its interpretation appropriate? all the source data underlying the results available to ensure full reproducibility? the conclusions drawn adequately supported by the results? competing interests were disclosed. Fertility, family planning, demography I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard, however I have significant reservations, as outlined above. replyRespond to this report Responses (1) 28 Jan 2022 Shiza Shiza, FP2020, Washington, 20006, USA Overall, we found your feedback to be incredibly helpful. Thank you for taking the time to make comments.

Output: pass


Input: Claim: Climate change is causing an increase in the frequency of extreme weather events. [SEP] Text: Developments in attribution science over the past two decades reinforce that statement by extending attribution statements about observed long-term climate change to encompass robust statements about the human influence on many types of individual extreme weather events. That includes heat waves, heavy precipitation events, and floods. Attribution methods for some classes of events have matured to the point where they could be operationalized to regularly inform the public about the current dangers of climate change. That would also greatly increase the number of events analyzed in that way and further understanding. Extreme weather happens everywhere, but most event-attribution studies have focused on events in nations that have the requisite human and computational resources. Groups like Attribution ( have begun to apply attribution science to significant weather events in low-income countries. Such organizations’ credibility is increased when they involve experts from those nations who better understand the details of local climate and associated impacts. The extension of attribution science to connect human increases to the socioeconomic damages and inequalities of extreme weather events is now underway. That work has the potential to inform low-income nations about their loss and damages, giving them the knowledge to negotiate for more assistance from recovery funds. 1. M. Allen, Nature 421, 891 (2003). Stott, D. Stone, M. Allen, Nature 432, 610 (2004). Masson-Delmotte et al. , eds. , 2021: Science Basis—I Contribution to the Report of the on Climate Change, Cambridge U. Press (2021). 4. G. J. van Oldenborgh et al. , Earth’s Future 10, e2021EF002271 (2022). Y. Philip et al. , Earth Syst. Dyn. 13, 1689 (2022). Bercos-Hickey, C. M. Patricola, W. A. Gallus Jr, J. Clim. 34, 8989 (2021). Clim. Extrem. 12, 24 (2016). D. Risser, M. F. Wehner, Geophys. Res. Lett. 44, 12457 (2017). M. Patricola et al. , Weather Clim. Extrem. 36, 100440 (2022). Commun. 13, 1905 (2022). J. van Oldenborgh et al. , Environ. Res. Lett. 12, 124009 (2017). S. Wang et al.

Output: corroborate


Input: Claim: All biodegradable plastics are safe for marine life and will not harm ocean ecosystems. [SEP] Text: , 2015; Thor & Dupont, 2015; et al. , 2016). ”Reviewer comment: Specific commentsL 63-66: This sentence suggests that there are few field (monitoring? ) studies on OA effects outside areas of unusually high CO2 levels. If this is so, I suggest to cite them and briefly summarize the state of the art here or in the following paragraph. This would give the reader a brief overview of what could be intensified/improved in the future. Otherwise, consider rephrasing this sentence and the sentence in l 462-464 of the conclusions. Also good to know here: Are there any monitoring data that allow the analysis of biological OA effects, and this just has not been done yet? Author response: As far as we know, linking chemical and biological monitoring data has not been done yet. We hope that this manuscript will stimulate such exercise after identification of suitable datasets but also motivate co-localized monitoring in stations that have already either chemical or biological observations. In the sentence 63-66, we referred to discrete observations and experimentation in the field. An example (Hall-Spencer et al. 2008) has been added Reviewer comment: L 75 ff Introduction: More explicitly name and address here and in the conclusions. Clearly point out and explain the contribution of ecophysiology/experimental studies to improving the framework with respect to OA here and in the conclusions (e. g. Hayes et al. 2015, Kissling et al. 2018, Pereira et al. 2013). I. e. what are the gaps this paper fills? Author response: The benefits of implementing our proposed response to the EOV-EBV framework have now been acknowledged in the introduction and conclusions. Reviewer comment: L 132: Replace “or” with “and”. Physiological data are important to attribute impacts to any environmental driver. Ecological data alone do not allow this. And vice versa. Author response: DoneReviewer comment: L 137 ff: State how these ecosystem traits and indicators relate to EOVs and EBVs (see 2013. Author response: DoneReviewer comment: L 410: Why was linear regression used? Drawn from toxicological concepts? If so, please cite respective literature. Author response : The dose response curve used for this exercise is not linear (Ventura et al.

Output: contrast


Input: Claim: Every ancient civilization has left behind detailed written records. [SEP] Text: Specific questions are addressed below. I suggest the authors focus the scope of this analysis and interpretation more specifically on the contraceptive use (or demand satisfied – see point #3) outcomes they can directly measure with DHS and MICS data used here. Though the authors say “we examine FP2020 country data and policies for signs of inequity” the data and methods in this paper do not allow it to comment directly on the focus of programs or policies. Such an analysis would require more comprehensive (not just selective) data on programmatic and policy decisions, with adequate lag time for analysis. We agree we would need additional data to discuss how program and policies impacted MCPR gains. Hence why it is not a focus of this paper and we removed any 2019. Is there a reason for using the Bangladesh 2014 DHS and not the 2017-18 survey? Unless there is a compelling reason related to the data, using the 2017-18 survey instead will provide a longer time lapse to better measure cumulative influence of FP2020. We only included surveys that were released by June 2019 and the Bangladesh 2017-18 had not been released by June 2019. The selective citing of policies related to increases in MCP among certain groups (e. g. , Malawi’s focus on youth) distracts from the overall finding/message (that FP2020 commitments, as they were applied within countries, did not seem to exacerbate inequalities writ large). These policies are also cited inconsistently – e. g. , credited for MCP gains among Malawi youth but no such policy is cited for the substantial gains among Malawi’s uneducated women – and thus come across as selective. On the first point, the overall focus of the paper is to assess if FP2020’s 120 million goal exacerbated inequities in countries. The focus of the paper is not on the country commitments themselves. We use the Malawi example to show that countries focused on implementing policies that supported reducing inequities. On the second point, we cited that Malawi prioritized youth access to family planning in their Strategy 2015-2020. The same policy also highlights the importance of education and prioritizing educational attainment among adolescent girls – we just did not cite this directly in the paper. I generally found the graphics challenging to read and interpret, with the key messages not clearly represented visually. Perhaps fewer and simpler graphics could better convey the main findings. We have added interpretation to the wealth and education graphics.

Output: pass