Input: Task: pass the claim using the given text. Claim: Every ancient civilization has left behind detailed written records. [SEP] Text: Unmarried sexually activevWe also assessed whether there had been an increase in MCP among unmarried sexually active women. Typically, the sample of women that are unmarried and sexually active in the last 30 days is small which makes testing for significant changes in MCP challenging (since a larger sample increases confidence in our estimates and the confidence intervals are tighter allowing for detectable changes). While none of the findings were significant, we did see an increase in modern method use in Malawi and Zimbabwe. DiscussionA criticism of the “120 million additional users” goal of the FP2020 partnership had been that countries and partners might prioritize easier to reach populations (e. g. with technical or political support from the FP2020 partnership) to meet this target, which exacerbates inequities. Overall, our findings suggest that between two surveys carried out since 2010, many countries saw MCP gains across different dimensions of equity, including residence, education, wealth, age, and marital status and do not suggest a focus on expanded coverage at the expense of equity. In most countries, MCP increased among rural women, and these gains were significant in seven African countries. In six countries, MCP gains were significant both among women with no education and in the lowest wealth group. MCP gains among young women aged 20–24 were seen in four African countries: Malawi, Senegal, Sierra Leone, and Uganda. In these four countries, MCP also significantly increased among young women aged 15–19. While we could not detect significant MCP changes among unmarried sexually active women, the country-specific trends indicate MCP is increasing among these women. All of the significant gains in MCP were made in African countries, and specifically Malawi, who experienced the most expansive growth across different dimensions of equity. Another possible criticism of the “120 million additional users” goal could be that the target would lead to a focus on more populous countries, but most of the gains in MCP were in African countries with populations far smaller than the those of several of the Asian countries in our sample. and Bangladesh rank in the top 10 most populous countries in the world. Yet, our analysis found that despite having larger populations, neither of these countries experienced the rapid MCP growth of several of the smaller countries. Compared to these Asian countries, most of the African countries in our analysis started at a lower MCP and thus had greater potential for increased modern contraceptive use. [SEP] Justify:

Output: The text is irrelevant to the claim as it discusses modern contraceptive practices in specific African countries and does not mention ancient civilizations or written records at all. It focuses on contemporary data and trends in maternal health care, which has no bearing on the historical claim regarding ancient civilizations.


Input: Task: corroborate the claim using the given text. Claim: Deforestation contributes to habitat loss and species extinction. [SEP] Text: Figure 2: Geographic distribution of areas with microendemic species of seed plants in Brazil according to (A) the number of endemic species, and (B) the classes of extinction risk in scenario 1, (C) scenario 2, and (D) scenario 3. Download full-size image DOI: 10. 7717/peerj. 7333/fig-2 Figure 3: The relative importance of habitat loss and climate change as threats to microendemic species of seed plants under different land-use change scenarios in the Brazilian phytogeographic domains: (A) scenario 1, (B) scenario 2, and (C) scenario 3. Download full-size image DOI: 10. 7717/peerj. 7333/fig-3 The number of areas and microendemics classified in each risk class varies according to the land-use scenario. In scenario 1, almost 70% (1,597 of the 2,354) of the microendemic species of seed plants in Brazil are under high extinction risk, 111 are in areas with both high climatic risk and high habitat loss, 926 are in areas with high habitat loss but low-to-medium climatic change risk, and 560 are in areas under high climatic risk and low-to-medium habitat loss (Fig. 2B). In scenario 2, the number of threatened species increases to 1,942 (c. 82%), with 342 in areas with both high climatic risk and high habitat loss, 1,271 in areas with high habitat loss but low-to-medium climatic change risk, and 329 in areas under high climatic risk and low-to-medium habitat loss (Fig. 2C). Finally, we found that 2,054 (c. 87%) microendemics are under high risk in scenario 3, with 381 in areas with both high climatic risk and high habitat loss, 1,383 in areas with high habitat loss but low-to-medium climatic change risk, and 290 in areas under high climatic risk and low-to-medium habitat loss (Fig. 2D). The proportion of microendemic species in each one of the four risk classes also varies across domains (Fig. 3). In all three scenarios, habitat loss is the primary factor threatening microendemics in the Atlantic Forest, Caatinga, and Pampa. [SEP] Justify:

Output: The text corroborates the claim by indicating that habitat loss is a primary factor threatening microendemic species of seed plants in Brazil. It details how different land-use change scenarios result in high extinction risks for species, stating that in scenario 1, almost 70% of microendemic species are under high extinction risk due to habitat loss. This aligns directly with the claim that deforestation contributes to habitat loss and species extinction.


Input: Task: pass the claim using the given text. Claim: The majority of deep-sea exploration is now conducted entirely by AUVs, with no human intervention required. [SEP] Text: Expenses of the Authority 1222–1224 Details 1224–1226 174. Borrowing power of the Authority 1224–1226 Details 1226–1228 175. Annual audit 1226–1228 Details 1228–1232 176. Legal status 1228–1232 Details 1232–1236 177. Privileges and immunities 1232–1236 Details 1236–1238 178. Immunity from legal process 1236–1238 Details 1238–1240 179. Immunity from search and any form of seizure 1238–1240 Details 1240–1241 180. Exemption from restrictions, regulations, controls and moratoria 1240–1241 Details 1241–1244 181. Archives and official communications of the Authority 1241–1244 Details 1244–1246 182. Privileges and immunities of certain persons connected with the Authority 1244–1246 Details 1246–1248 183. Exemption from taxes and customs duties 1246–1248 Details 1248–1249 184. Suspension of the exercise of voting rights 1248–1249 Details 1249–1250 185. Suspension of exercise of rights and privileges of membership 1249–1250 Details 1250–1277 Section 5. Settlement of disputes and advisory opinions 1250–1277 1250–1254 186. Sea-Chamber of the for the Law of the Sea 1250–1254 Details 1254–1261 187. Jurisdiction of the Chamber 1254–1261 Details 1261–1266 188. Submission of disputes to a special chamber of the for the Law of the Sea or an ad hoc chamber of the Chamber or to binding commercial arbitration 1261–1266 Details 1266–1271 189. Limitation on jurisdiction with regard to decisions of the Authority 1266–1271 Details 1271–1274 190. Participation and appearance of sponsoring in proceedings 1271–1274 Details 1274–1277 191. Advisory opinions 1274–1277 Details 1277–1605 Part XII: Protection and preservation of the marine environment 1277–1605 1277–1328 Section 1. General provisions 1277–1328 1277–1287 192. General obligation 1277–1287 Details 1287–1295 193. [SEP] Justify:

Output: The text is irrelevant to the claim as it contains administrative and legislative details regarding the Authority and does not discuss deep-sea exploration or the use of AUVs. Therefore, it cannot support, contrast, or provide any pertinent information regarding the claim.


Input: Task: pass the claim using the given text. Claim: Every ancient civilization has left behind detailed written records. [SEP] Text: However, it is worth noting Pakistan had more room to grow than Malawi, who experienced the most overall MCP growth and saw growth across different equity dimensions. Additionally, given all countries in our analysis are still experiencing population growth and thus an increasing population of women of reproductive age, even countries such as Bangladesh, Nepal, and Pakistan, that did not have significant levels of MCP growth, were providing contraceptive services to a greater number of women of reproductive age without experiencing declines in equity. Given that countries could either experience (a) rapid MCP growth (because they started at a lower MCP in the middle of the S-curve growth pattern19) or (b) sustained modern contraception users (meaning they continue to add more users of modern contraception due to population growth and a slower increase in MCP), supportive country-specific policies and commitments that focused on expanding services and improving equity could be at the nexus of increasing and/or retaining modern contraceptive users without exacerbating inequities. In order to sustain its high MCP, government and development partners in Bangladesh successfully focused on geographic inequities; both the Sylhet and Chittagong divisions had the lowest MCP in 2011 and saw significant increase in the 2014 DHS (2 years after Bangladesh committed to improving family planning services in these two divisions). Similarly, Malawi successfully prioritized young people in its commitments and policies. In fact, Malawi was one of four countries where MCP gains among the youngest women of reproductive age (15–19) were significant. Malawi also had the largest MCP gain among women with no education – at over 16%20–22. As the family planning community begins to look ahead to the FP2030 partnership, this analysis can help inform the emerging FP2030 family planning framework, which includes equity as a guiding principle23. Helping family planning stakeholders understand whether the ambitious goal of the FP2020 partnership impacted equity will be critically important in determining how to establish goals and operationalize equity in the future family planning partnership. From our findings, we interpret the impact of the FP2020 partnership on equity to be positive or at a minimum neutral, and do not see signs of exacerbated inequality within countries. Countries engaged with the partnership through country-specific commitments, and those that set country-specific priorities to reduce inequitable access to modern contraceptive counseling and services, reaped the benefits. [SEP] Justify:

Output: The text does not relate to the claim about ancient civilizations and their written records. Instead, it discusses modern countries and contraception services, which is entirely different from the topic of historical documentation.


Input: Task: corroborate the claim using the given text. Claim: Deforestation contributes to habitat loss and species extinction. [SEP] Text: In the Amazon and Cerrado, climate change is the primary factor threatening microendemics in scenario 1, but the combination of climate change and habitat loss is the primary threat driver in scenarios 2 and 3 (Fig. 3). In Pantanal, the species under risk are mainly affected by the combination of habitat loss and climate change. In scenario 1, the number of species under risk is higher than the number of species with low risk, except in Caatinga and Pampa (Fig. 3). However, in scenarios 2 and 3, the number of species under risk is always higher than the number of species with low risk across all domains (Fig. 3). Among the 2,354 microendemic species analyzed in this paper, only 338 (14. 3%) have been included in the official Brazilian plant (of the Environment, 2014). As expected, most of these species, ranging from 61. 2% in scenario 1 to 86. 9% in scenario 3, are also classified as having high extinction risk in our analyses (Table 1). If we count the number of microendemics that are not on the official List but that are projected to have high extinction risk, we find the following numbers: scenario 1, 1,391 species; scenario 2, 1,665 species; and scenario 3, 2,017 species. Table 1: Number of microendemic species of seed plants in Brazil listed and not listed on the official List of threatened plant species (Brasil, 2014) according to their extinction risk classification (Fig. 1) under three different land-use scenarios. risk Low risk Red list Not listed Red list Not listed Immediate conservation action 207 1390 131 626 Long-term conservation action 278 1664 60 352 No conservation action 294 1760 44 256 DOI: 10. 7717/peerj. 7333/table-1 to the land-use scenario, the number of microendemics threatened by habitat loss, climate change, or by both factors in Brazil is between 2. 86 and 3. 68 times higher than the number of Brazilian plant species classified as threatened (558) by the IUCN global plant assessment (IUCN, 2019) but comparable (1. 32 and 1. 02 times smaller) to the total number of seed plant species classified as threatened (2,113) on the official List (of the Environment, 2014). [SEP] Justify:

Output: The text corroborates the claim by stating that habitat loss, along with climate change, is a primary threat to microendemic species in Brazil. It mentions that the number of microendemics threatened by habitat loss and climate change is significantly higher than the number of species classified as threatened, reinforcing the idea that deforestation (a contributor to habitat loss) is a critical factor in species extinction risk.


Input: Task: pass the claim using the given text. Claim: Insect farming requires significantly less land and water than traditional livestock farming. [SEP] Text: 2018;15(2):302-316. DOI: 10. 1007/s10393-018-1312-y20. . Current drivers and future directions of global livestock disease dynamics. Proceedings of the of Sciences. 2011;110(52):20871-20877. DOI: 10. 1073/pnas. 101295310821. Brooks-. Eight challenges in modelling infectious livestock diseases. Epidemics. 2015;10:1-5. DOI: 10. 1016/j. epidem. 2014. 08. 00522. . Quantifying the impact of foot and mouth disease on tourism and the UK economy. Tourism Economics. 2003;9(4):449-465. DOI: 10. 5367/00000000332266322123. . Uptake of rabies control measures by dog owners in Flores Island, Indonesia. . 2015;9(3). DOI: 10. 1371/journal. pntd. 000358924. Response to a Rabies Epidemic, Bali, Indonesia, 2008-2011. Diseases. 2013;19(4):648-651. DOI: 10. 3201/eid1904. 12038025. Food and of the (FAO). The impact of political and social instability on animal health. FAO. 2002;153:4726. Food and of the (FAO). FAO/OIE progressive control pathway for foot and mouth disease. 2011. Available from: www. fao. org/fileadmin/user_upload/eufmd/docs/PCP/PCP_Guidelines_Eng_2012web. pdf [Accessed: 08 January 2020]27. Evans B. The social and political impact of animal diseases. Veterinaria Italiana. 2006;42(4):399-40628. Kaplan M. Social effects of animal diseases in developing countries. Bulletin of the Atomic Scientists. 1966;22(9):15-21. DOI: 10. 1080/00963402. 1966. 1145498529. Crimes D, Enticott G. Assessing the social and psychological impacts of endemic animal disease amongst farmers. Frontiers in Veterinary Science. 2019;6. DOI: 10. 3389/fvets. 2019. 0034230. Robertson ID. [SEP] Justify:

Output: The text is irrelevant to the claim as it discusses various topics related to livestock diseases, their social impacts, and political implications, without mentioning insect farming or a comparison of land and water usage between insect farming and traditional livestock farming. Therefore, it does not provide any supporting or contrasting information related to the claim.


Input: Task: pass the claim using the given text. Claim: Every ancient civilization has left behind detailed written records. [SEP] Text: While our analysis provides policy-relevant findings for the next family planning partnership, it had some limitations that should be noted. With our analysis confounding is likely and while regression approaches can mitigate against confounding, our aim was not to discern socio-demographic specific effect sizes or confirm associations. For example, our main objective was not to understand how different socio-demographic factors such as being wealthy versus poor increase the odds or probability of modern contraceptive use. Our primary objective was to understand if MCP significantly increased across different dimensions of inequities between two surveys, and a simple weighted bivariate analysis sufficed. Furthermore, with a simpler methodological approach (which is also more conservative in testing for significance), interpretability of findings is greater. Household surveys such as the MICS and DHS are not powered to detect significant changes among a relatively small portion of unmarried, married sexually active women; if changes among this sub-population of women are of special interest for family planning programming, other methods need to be employed to more precisely estimate their modern contraceptive use. Furthermore, in some countries the proportion of women in “no education” or “poorest” groups declined over time. It’s unclear whether this aided countries in providing family planning services to these groups. Our analyis does not address this. This analysis addresses if FP2020’s overall “120 million additional users” goals led to the priorizitzation of easier to reach populations and exacterbated inequities; our findings can be used to inform the FP2030 partnership and reinforce that country-specific commitments, policies, and programming is likley to have the largest net effect on increasing or retaining modern contraceptive users and leaving no one behind. [SEP] Justify:

Output: The text is irrelevant to the claim about ancient civilizations having left detailed written records. It discusses modern family planning efforts and methodologies in data analysis without addressing historical written records in any capacity.


Input: Task: corroborate the claim using the given text. Claim: Deforestation contributes to habitat loss and species extinction. [SEP] Text: Although the number of high-extinction risk species is smaller than the number of species on the official List, these two lists show a thin overlap (c. 8%), suggesting that current conservation assessments, both at national and global levels, underestimate the actual number of plants at extinction risk by a high margin. Moreover, our findings fit well with studies in other regions of the world, demonstrating that species with narrow distributions have not had their extinction risk adequately assessed by traditional conservation assessments (Wulff et al. , 2013; Ocampo-Peñuela et al. , 2016; Caesar, Grandcolas & Pellens, 2017). Microendemic plants are not evenly distributed across Brazil; they seem to be concentrated in relatively small watersheds where the combination of topography, climate, and soil favors both the generation and the accumulation of endemic species over time. This pattern is similar to the ones reported in other countries with high numbers of narrowly distributed species (Borchsenius, 1997; Wulff et al. , 2013). In Brazil, such regions are mostly mountains associated with stable or heterogeneous bioclimatic domains along the (Carnaval et al. , 2014) or with old, climatically buffered, infertile landscapes (OCBILs) in the Cerrado and Caatinga highlands (Conceição et al. , 2016; Silveira et al. , 2016). Habitat loss is the predominant factor increasing the extinction risk of narrowly distributed species of seed plants in Brazil. However, climate change (alone or interacting with habitat loss) can also increase the extinction risk of a substantial number of species. Despite the uncertainties on how climate is going to change ecosystems within areas with microendemics (Torres & Marengo, 2014), as well as how these microendemics will react to the effects of such changes, recent studies have all indicated that plant species with small ranges and narrow habitat p16. 2% by 2100 if no conservation action takes place. Low habitat coverage due to insufficient protection increases extinction risk because it reduces the adaptive capacity of species to cope with climate change (Watson, Iwamura & Butt, 2013; Eigenbrod et al. , 2015). Therefore, this group of microendemics is the most threatened, and the areas where they live are top priorities for more studies and conservation intervention. [SEP] Justify:

Output: The text corroborates the claim by stating that habitat loss is the predominant factor increasing the extinction risk of narrowly distributed species of seed plants in Brazil. This supports the argument that habitat loss, often a result of deforestation, leads directly to increased extinction risk among species.


Input: Task: contrast the claim using the given text. Claim: Eating insects will completely replace meat consumption globally within the next decade. [SEP] Text: The analyses were conducted using weighting variables (primary sampling unit, stratum and sampling weight) to account for the complex survey design. Data were analyzed separately by gender, per capita family income and age group. For all analyses, STATA statistical software package version 10 [28] was used and a p<0. 05 was considered statistically significant. ResultsThe unweighted sample comprised a total of 4023 people from both data collection, 49% were male in 2003 and 44% were male in 2008; mean age was 41±24 years in 2003 and 37±26 years in 2008; mean per capita family income was U$$167 in 2003 and U$$383 in 2008. The proportions of men and women were the same in each age group and in each tertile of per capita income in both surveys. The population in the study showed an increase in consumption of the different types of meat from 2003 to 2008. Women, elderly and low-income groups were the only ones who did not show higher red meat consumption in 2008 than in 2003. There was an increase in white and processed meat intake for the entire population (Table 1). Adolescents and men also showed an increase in beef intake, while the elderly showed a decrease. Fish consumption rose for all groups but for the elderly and individuals with intermediary income. Intake of pork did not increase among the elderly and individuals with low and intermediary income. Poultry consumption increased for the entire population (Table 2). Download: PPTPowerPoint slidePNGlarger imageTIFForiginal imageTable 1. Dietary intake of total meat, red meat, processed and white meat (g/day) according to age, gender, per capita family income and year studied. São Paulo. 2013. Download: PPTPowerPoint slidePNGlarger imageTIFForiginal imageTable 2. Beef, pork, poultry and fish intake (g/day) according to age group, gender, per capita family income and year studied. São Paulo. 2013. was a 20% increase in average meat consumption, with a greater increase in white meat intake (35%) and lower increase in red meat intake (11%). Processed meat intake also increased during the periods studied (20%), especially among adolescents (29%). As for the origin of the meat, the increase in consumption was greater for fish (46%), followed by poultry (30%), pork (30%) and beef (1%). [SEP] Justify:

Output: The text contrasts the claim by providing data that indicates an overall increase in meat consumption from 2003 to 2008, suggesting that rather than being replaced, meat consumption is on the rise across various demographics. Specifically, it mentions significant increases in different types of meat consumption — white meat by 35%, processed meat by 20%, and fish by 46% — indicating a trend of increasing meat intake, which undermines the possibility of insects fully replacing meat consumption within the next decade.


Input: Task: pass the claim using the given text. Claim: Every ancient civilization has left behind detailed written records. [SEP] Text: Data availabilityUnderlying dataDHSData used in this study are from the HR and IR datasets of the Bangladesh 2014 and 2011 DHS; the HR and IR datasets of the Burundi 2016–17 and 2012 DHS; the HR and IR datasets of the Ethiopia 2016 and 2011 DHS; the HR and IR datasets of the Haiti 2016–17 and 2012 DHS; the HR and IR datasets of the Malawi 2015–16 and 2012 DHS; the HR and IR datasets of the Nepal 2016 and 2011 DHS; the HR and IR datasets of the Pakistan 2017–28 and 2012–23 DHS; the HR and IR datasets of the Senegal 2017 and 2012 DHS; the HR and IR datasets of the Uganda 2016 and 2011 DHS; and the HR and IR datasets of the 2015 and 2010–11 Zimbabwe DHS, available from the DHS website. Access to the dataset requires registration and is granted only for legitimate research purposes. A guide for how to apply for dataset access is available at: used in this study are from the households (HH) and women (WM) datasets of the 2010, 2016, MICS, available from the MICS website. Access to the dataset requires registration and is granted only for legitimate research purposes. Questions about data access can be directed to mics@unicef. org. Extended dataAnalysis code available from: analysis code at time of publication:. Footnotes i Data only available for surveys where unmarried women were interviewed. ii Surveys with microdata available for use by June 2019. iii Vietnam met the criteria but was excluded from this analysis since Vietnam did not make a commitment to FP2020 until 2016 and the two surveys only overlapped the first two years of the FP2020 initiative (2010 MICS and 2014 MICS). iv This does not apply to countries with ever-married samples, including Bangladesh and Pakistan. For both Pakistan and Bangladesh, the analysis is only reflective of married women. v This does not apply to countries with ever-married samples, including for Bangladesh and Pakistan. Unmarried sexually active are women that are not-in-union nor married and were sexually active in the last month. recommended1. Global Advocates: 's First. Center for website. 29, 2019. Reference Source2. : Achieving the goal of the on by adhering to voluntary, rights-based family planning: what can we learn from past experiences with coercion? Health. 2014; 40(4): 206–214. [SEP] Justify:

Output: The text is irrelevant to the claim as it focuses on data availability from various demographic surveys conducted by the DHS and MICS organizations. There is no mention of ancient civilizations or their written records.


Input: Task: corroborate the claim using the given text. Claim: Deforestation contributes to habitat loss and species extinction. [SEP] Text: The relative contribution of habitat loss and climate change as extinction drivers of microendemics varies across domains. Habitat loss is the most critical factor in the Atlantic Forest, where most of the natural ecosystems were lost due to the replacement of natural ecosystems by agriculture fields and urban areas (Tabarelli et al. , 2005). This coastal region has a relatively low climate change risk when compared to other regions in Brazil (Torres & Marengo, 2014). The risk caused by climate change is higher in areas with microendemics in the Amazon, in the high plateaus in the Cerrado and Caatinga, and in Pantanal. These areas show high climate change risk through different GHG forcing scenarios and Model datasets (Torres & Marengo, 2014) and are still relatively intact, although habitat loss is projected to increase in these areas until 2100. Habitat loss and climate change can drive the extinction of microendemics in areas of the southwestern Atlantic Forest, the southern Cerrado, and along the Amazon’s deforestation arch. Most of these areas have recently been modified by human activities as a consequence of the ongoing expansion process of large-scale commercial agriculture (Beuchle et al. , 2015). Projecting the extinction risk of narrowly distributed species due to habitat loss and climate change has been limited to date because they are known only from a few localities, which makes the use of species distribution models unreliable. Although our analysis addressed some of these shortcomings by shifting the focus from species ranges to the areas where these species live, our projections have limitations similar to most studies using taxonomic and distribution datasets in tropical regions. The first limitation is the reliance on information on the taxonomy and distribution of species to identify areas with microendemics. However, by relying on the previous collective effort of botanists to identify and map rare species of seed plants in Brazil (Giulietti et al. , 2009) and counting on electronic journals and databases to update the original dataset, we have been able to overcome some of these challenges. Nevertheless, our analysis, such as any other evidence-based projection, should be updated and evaluated over time. A second limitation of our approach is that it does not lead to a deep understanding of the complex mechanisms by which habitat loss and climate change together or separately would increase the extinction risk of narrowly distributed species. [SEP] Justify:

Output: The text corroborates the claim by discussing how habitat loss, primarily driven by agricultural expansion and urbanization, has critically impacted ecosystems in the Atlantic Forest and is projected to lead to increased extinction risks for microendemic species. It highlights that 'habitat loss is the most critical factor' in areas greatly affected by deforestation, thus supporting the assertion that deforestation contributes to habitat loss and species extinction.


Input: Task: contrast the claim using the given text. Claim: Eating insects will completely replace meat consumption globally within the next decade. [SEP] Text: Among the most frequently consumed processed meats by the citizens of São Paulo, sausages and frankfurter represented 60% of the processed meat intake in both the periods studied, and were followed by ham, industrialized breaded chicken and mortadella (data not shown). In 2003, 72% of residents of the city of São Paulo exceeded red and processed meat intake recommendations from the WCRF, and in 2008, this number was 74% (a non significant variation). The proportion of individuals from the different age groups and genders that exceeded red and processed meat intake recommendations was the same in both studies (data not shown). DiscussionWe observed a significant increase in meat consumption in the city of São Paulo from 2003 to 2008, especially in total meat, poultry, white and processed meat intakes that increased regardless of gender and per capita family income. It is known that there is an increasing tendency of poultry production in Brazil, and this might be a good factor once poultry has leaner meat and therefore can improve diet quality [1], [29]. However, there is also an increased tendency in producing processed meats that have higher fat contents, apart from having potentially carcinogenic substances such as nitrites and nitrates, and sodium [1], [4]. These increasing intake tendencies shown in this study can be explained due to the low prices of poultry and processed meats [30], the increasing poultry and processed meat production, the Brazil economic stability over the past few years, what increased the population purchasing power [31], and also because meat is a typical food within Brazilian eating habits and desired by most of the population. We observed that red meat and beef did not show a significant consumption increase in any of the analyzed categories, but were the most consumed in both periods. Fish, on the contrary, was the least consumed by the city's residents. We found similar data to the tendency observed in São Paulo in the last (1987–1988; 1995–1996; 2002–2003; 2008–2009). Beef had the greatest energy contribution in the Brazilian population diet in the periods studied, but underwent a decline over the last years. Meanwhile, poultry consumption showed a progressive increase throughout the whole period (150%). Fish intake had low and constant contribution, less than 1% [32], [33]. In regards to meat consumption around the world, available data from the Food and show an increasing number in daily total meat intake in developed countries such as the US [13] and the [2]. [SEP] Justify:

Output: The text contrasts the claim by providing evidence of increasing meat consumption in São Paulo, specifically noting that processed meats and poultry have shown significant growth in intake. It mentions the cultural significance of meat consumption in Brazil and that red meat, despite a decline in its contribution, remains the most consumed. This indicates that rather than a shift toward insects as a replacement for meat, traditional meat consumption is on the rise.


Input: Task: pass the claim using the given text. Claim: Every ancient civilization has left behind detailed written records. [SEP] Text: Pub| Text 3. 2020 (FP2020): Contributions of FP2020 in advancing rights-based family planning – upholding and advancing the promises of Cairo. Washington, DC: FP2020; 2019. 29, 2019. Reference Source4. Does your the Test? 2020 website. 28, 2019. Reference Source5. United Nations: UN Resolution 70/1 – Transforming our world: the 2030 Agenda for Sustainable Development. City: UN; 2015. 28, 2019. Reference Source6. (FPET). Track20 website. 28, 2019. Reference Source7. Assaf S, Wang W: in Fertility P71. Rockville, MD. 30, 2019. Reference Source8. Ortayli N, Malarcher S: Equity Analysis: Benefits from Programs. Plann. 2010; 41(2): 101–108. Pub| Text 9. : Unwanted fertility among the poor: An inequity? Health Organ. 2007; 85(2): 100–107. Pub| Text | Text 10. : Did equity of reproductive and maternal health service coverage increase during the MDG era? An analysis of trends and determinants across 74 low- and middle-income countries. PLoS One. 2015; 10(9): e0134905. Pub| Text | Text 11. Blas E, Kurup AS: Equity, social determinants and public health programmes. Geneva: WHO; 2010; 2, 2019. Reference Source12. Gwatkin DR: 10 best resources on. . . health equity. Plan. 2007; 22(5): 348–351. Pub| Text 13. O': Applying an equity lens to interventions: using ensures consideration of socially stratifying factors to illuminate inequities in health. J Clin Epidemiol. 2014; 67(1): 56–64. Pub| Text 14. : Analyses of inequalities in RMNCH: rising to the challenge of the SDGs. BMJ Global Health. 2019; 4(Suppl 1): e001295. Pub| Text | Text 15. : Absolute Poverty, Fertility P48. Reference Source16. Ross J: Improved reproductive health equity between the poor and the rich: An analysis of trends in 46 low- and middle-income countries. Sci Pract. 2015; 3(3): 419–445. Pub| Text | Text 17. [SEP] Justify:

Output: The text is irrelevant to the claim regarding ancient civilizations and their written records. The content primarily discusses various references and reports about health equity and family planning without addressing any aspects of ancient civilizations or their historical documentation.


Input: Task: corroborate the claim using the given text. Claim: Deforestation contributes to habitat loss and species extinction. [SEP] Text: Mechanistic studies are more reliable when they are conducted on small rather than large scales (Oliver & Morecroft, 2014). By pinpointing the areas with plant microendemics coupled with habitat loss and climate change estimates, we hope to help researchers who are interested in extinction risks and conservation make better site selections for experiments. Finally, the third limitation of our study is that it assessed two extinction drivers (habitat loss and climate change). Thus, the impacts of drivers such as invasive species, pollution, and overexploitation on narrowly distributed native plants continue to be unchecked (Almeida et al. , 2015; Scarano & Silva, 2018). Despite all the limitations above, the analytical approach used here is simple and, at the same time, robust and replicable enough to help conservationists and decision makers in tropical countries to detect essential areas for conservation and assess the extinction risks of narrowly distributed species. Most conservation policies in Brazil and other tropical countries do not include considerations of climate change (Kasecker et al. , 2018; Silva & Prasad, 2019). Consequently, they are mostly retrospective; that is, they seek to use the historical conditions of the natural ecosystems as benchmarks (Magness et al. , 2011). Because climate change is irreversible, current policies should also be prospective. In other words, they should work proactively to facilitate the transition of the species and ecosystems to a new set of climatic conditions (Magness et al. , 2011). The decision on what strategy to use depends on the current state of habitat loss and climate change risk of the places where species live. In general, retrospective strategies are suitable for those species endemic to areas with low risk or that have habitat loss as a major threat. For species endemic to areas with low risk, conservation through protected areas is the most effective action. For species endemic to areas where habitat loss is the primary threat, the efforts should be focused on conserving the remaining natural vegetation as much as possible through establishing protected areas and restoring vegetation in critical places. Prospective conservation strategies are recommended for species endemic to areas that are threatened exclusively by climate change or by a combination of climate change and habitat loss. Hence, to protect species endemic to areas where the major threat is climate change, governments should establish conservation networks inside and beyond the areas with microendemics that facilitate the natural adaptation of the species and their habitats to the new climatic conditions. [SEP] Justify:

Output: The text corroborates the claim by discussing habitat loss as a significant threat to species, particularly those endemic to areas affected by climate change and habitat loss. It emphasizes the importance of conserving natural vegetation and establishing protected areas to mitigate habitat loss, which supports the idea that deforestation contributes to habitat loss and, consequently, species extinction.


Input: Task: contrast the claim using the given text. Claim: Eating insects will completely replace meat consumption globally within the next decade. [SEP] Text: We also noticed an increase in white meat intake (from 25 g to 55 g/day) and decrease in red meat intake (from 105 g to 85 g/day) in the US from 1999 to 2007 [13]. Total meat and red meat intake in São Paulo proved to be higher or similar than those found in developed countries such as the US [13], Germany, Ireland, Spain and the Netherlands [2]. That is, the citizens of São Paulo consumed more red meat than those in developed countries. For processed meat, the intake was the same as that of the US [13] and greater than that of Ireland, Greece and Italy [4]. Meat provides an important source of protein and micronutrients for humans, however excessive red and processed meat consumption is known to be associated to an increase in risk of colon and rectal cancer [4]. It is known that the intake of 50 g of processed meat a day increases the risk of CVD by 42%, and of diabetes by 19% in the US [3]. In our study, we noticed that almost 75% of the population showed excessive red and processed meat intake, what may increase the prevalence of these diseases in the city of São Paulo. Red and processed meat intake among adolescents was also high, what may contribute to increased risk of cancer later in life. cohort study showed that processed meat intake during adolescence increased the risk of colon and rectal cancer [34] in 25% among adolescents with high consumption. Cancer incidence has been increasing significantly for the past decades and was one of the main causes of death from 1980 to 2010, in the city of São Paulo. Colon and rectal cancer is the third most frequent type of cancer among men and women. From 1997 to 2008 almost 17. 0 thousand new cases were diagnosed in men; and at the same time there were 18. 5 thousand new cases among women. The incidence of this type of cancer increased in 24% and 39% among men and women, respectively, from 2003 to 2008 [35]. It is well known that diet has an important role in preventing and causing this type of cancer and there is convincing evidence of the relationship among red and processed meats increase in risks of colon and rectal cancer [4]. [SEP] Justify:

Output: The text contrasts the claim by highlighting current meat consumption patterns and health concerns related to red and processed meat. It mentions that meat intake remains significant, particularly red meat, and outlines the associated health risks, suggesting that traditional meat consumption continues to be important for protein and micronutrients. Therefore, the assertion that eating insects will completely replace meat consumption within the decade does not align with the realities presented in the text.


Input: Task: pass the claim using the given text. Claim: Every ancient civilization has left behind detailed written records. [SEP] Text: for (USAID):Intertemporal comparisons of poverty and wealth with DHS data: A harmonized asset index approach. Washington, DC: USAID; 2014; 2, 2019. Reference Source18. Smits J, Steendijk R: (IWI). Res. 2015; 122: 65–85. Text 19. The S-Curve: Putting mCPR Growth into Context. 2, 2020. Reference Source20. 2012 on Family Planning, Summaries of Commitments. 2020 website. 2013; 19, 2020. Reference Source21. Ministry of Health, Malawi: Evaluation of Youth-Services in Malawi. Malawi: Evidence 2 Action; 2014. 9, 2020. Reference Source22. Ministry of Health, Malawi: Ministry of Health: 2015-2020. 9, 2020. Reference Source23. Beyond 2020: A for Post-2020. 2020 website. 19, 2020. Reference Source24. familyplanning2020: familyplanning2020/NOLB: NOLB Code (Version v1. 0). Zenodo. 2021. Comments on this 10. 12688/gatesopenres. 13339. 2 version 1 Published: 28 Jul 2021, 5:114 Copyright © 2021 et al. This is an open access 10. 12688/gatesopenres. 13339. 1) NOTE: it is important to ensure the information in square brackets after the title is included in all 10. 21956/gatesopenres. 14582. r31004) The direct URL for this report is: This paper seeks to as answer several critical questions on the impact of FP2020’s goal of 120 million additional users (“120x20”), specifically whether certain groups of women were systematically left behind. I believe it makes an important contribution by providing. . . Continue reading paper seeks to as answer several critical questions on the impact of FP2020’s goal of 120 million additional users (“120x20”), specifically whether certain groups of women were systematically left behind. I believe it makes an important contribution by providing an early indication that groups of women who are generally disadvantaged do not appear to have been left behind in FP2020 commitment countries. However, I think this is fundamentally different from questions around equity. [SEP] Justify:

Output: The text is irrelevant to the claim as it discusses various reports and topics related to family planning and the FP2020 initiative without mentioning anything about ancient civilizations or their written records.


Input: Task: corroborate the claim using the given text. Claim: Deforestation contributes to habitat loss and species extinction. [SEP] Text: There are still space and time to design and implement new climate-resilient conservation networks to protect these species because such areas remain relatively intact. In contrast, for species endemic to areas that are simultaneously affected by habitat loss and climate change, governments should deploy more complex management solutions to facilitate their maintenance under new climate conditions in a landscape dominated mostly by human-made ecosystems. Such solutions should include a mix of protected areas, ecological restoration in critical sites and corridors, active manipulation of habitat conditions to better match species requirements, and ex-situ conservation techniques, such as cryopreservation, seed banking, tissue culture, and cultivation collections (Havens et al. , 2006). The adoption of retrospective and prospective conservation strategies demands governance mechanisms that integrate conservation and national climate change strategies into a coherent policy framework. However, despite all the global efforts to promote policy coherence and integration, the policies regarding biodiversity conservation and climate change at the national scale continue to be drifting apart. We suggest that in tropical countries such as Brazil, where resources are scarce and sound environmental governance continues to be an issue, integrating biodiversity conservation and climate change policies (both mitigation and adaptation) is the most effective solution to achieve win-win social and environmental solutions while halting species extinction. documented 2,354 narrowly distributed species of seed plants in 776 areas that altogether cover 17. 5% of Brazil. From 70% to 85% of these species are projected to face high extinction risk due to habitat loss and/or climate change. The importance of climate change and habitat loss as drivers of species extinction varies across domains, and this variation demands the adoption of retrospective and prospective conservation strategies. At the national level, we suggest that the integration and coherence of biodiversity conservation and climate change policies is a critical step to safeguard an irreplaceable portion of Brazilian biodiversity. The maps used to estimate extinction risk of microendemic species of seed plants in Brazil (a) phytogeographic domains (IBGE, 2004 modified by Silva, Leal & Tabarelli, 2017); (b) fifth-order watersheds ( (c) cumulative habitat loss in 2014 (IBGE, 2017); (d) (RCCI). DOI: 10. 7717/peerj. [SEP] Justify:

Output: The text corroborates the claim by detailing the impacts of habitat loss, particularly due to deforestation, on species extinction. It states that 'from 70% to 85% of these species are projected to face high extinction risk due to habitat loss and/or climate change.' This directly supports the claim that deforestation (a major cause of habitat loss) contributes to the risk of species extinction.


Input: Task: pass the claim using the given text. Claim: The majority of the world's population will soon switch to insect-based diets as the primary source of protein. [SEP] Text: For each diet, ion quantities in flies were plotted against the ion quantities in their respective fruit (on a log scale), and their correlation (and associated R²) was computed through linear modeling. Additionally, we investigated the intersections of origin (and their degrees) of these diet-specific ions, both in fruits and flies, to gain insight about their specificity. Finally, to evaluate the respective power of our qualitative and quantitative datasets to correctly classify flies according to their diet, we randomly sampled ions in batches of various sizes (10–10,000 ions; each random sampling repeated 10,000 times). We then computed (i) the proportion of flies correctly classified to their diet and (ii) Information (AMI, a comparison index between clustering; Vinh et al. , 2010) for each sample size for both quantitative and qualitative datasets. AMI was computed using the aricode R package (Chiquet et al. , 2020). Identification of metabolites Request a detailed protocol We attempted to identify two different categories of metabolites. First, we tried to identify metabolites from the compact’ list of ions associated with diet in flies (from our analysis). Second, we investigated 50 major ions in each fruit (i. e. with the highest peak area), potentially corresponding to major metabolites in each fruit. Metabolites were identified based on molecular formula generated from accurate mass measurements, given the fact that mass spectrometry conditions were chosen to obtain fragments by in-source fragmentation, in addition to pseudo-molecular ions. In addition, MS/MS analyses were performed with all samples for fragmentation-based metabolite annotation. Metabolite identifications were proposed based on expertized analysis of the corresponding mass spectra and fragmentation patterns, in comparison with authentic standards when available, with the MassBank ( mzCloud ( and Chem-Spider ( mass spectral databases as well as with the published literature. Following this process, an identification confidence level was assigned to all identified metabolites, according to Schymanski et al. , 2014. This has allowed the putative identification of 71 food-associated metabolites detected in flies, 30 of which were confirmed with authentic standards. Finally, for each identified compound in each fruit, a survey of the published literature was performed to check for previous identification of this compound in this fruit. Metabolite identification information as well as related literature 1. [SEP] Justify:

Output: The text is irrelevant to the claim as it discusses a study involving metabolite identification in fruit and flies and does not mention insect-based diets, population dietary shifts, or protein sources. Therefore, it does not provide any corroborating or contrasting information related to the claim.


Input: Task: pass the claim using the given text. Claim: Every ancient civilization has left behind detailed written records. [SEP] Text: see it, this paper’s contribution is not as the definitive answer to the elusive “equity” question in FP but rather to ascertain whether data from a select set of commitment countries indicates that progress under FP2020 exacerbated gaps in use between advantaged and disadvantaged groups. While it is difficult to draw many clear conclusions from this analysis (as nearly all results are inconsistent across countries), the results presented indicate that among FP2020 commitment countries there were not systematically greater MCP gains by the most advantaged women. This is a substantial finding that is almost buried under discussions about equity, programs and policies to which the data used does not directly speak. To strengthen this paper and to make the results and interpretation more robust, I suggest the authors stick more closely to the stated and important goal of ascertaining whether “increases in mCPR did not vary significantly in more disadvantaged groups” since the 2012 London Summit. Detailed feedback: 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. I question the appropriateness of MCP growth for this analysis. Without some underlying or contextual measure of demand or access, using MCP alone to measure equity implies that there is some ideal level of MCP across all populations – and the higher, the better (in contradiction to the FP2020 principles of agency and autonomy referenced). Could the authors look at changes in demand satisfied, arguably a more appropriate measure of equity given the different underlying levels of demand for contraception among population sub-groups? Flawed though unmet need is as a direct measure of demand for contraception, including it as a backdrop here (via demand satisfied) would better contextualize “equitable” FP changes. If the authors choose to stick with MCP change, this should be more clearly addressed as an (acceptable) limitation. It would also be good to better contextualize demand/unmet need in the context of the FP2020 goal (i. e. [SEP] Justify:

Output: The text is irrelevant to the claim as it discusses issues related to family planning, data analysis, and equity, without mentioning ancient civilizations or written records.


Input: Task: corroborate the claim using the given text. Claim: Deforestation contributes to habitat loss and species extinction. [SEP] Text: policy requires reliable estimates of extinction rates that consider the interactions between population size (N) and habitat area. Current approaches to estimating extinction from the endemics–area relationship (EAR) estimate only the minimum number of species that can become extinct because of habitat loss (instantaneous extinction). EARs will therefore underestimate extinction if small populations and/or habitat area (SPHA) commit species to future extinction. We demonstrate this mathematically, by assuming species require a minimum population size of two individuals, and by randomly sampling habitat loss within stem-mapped forest plots. We then develop a general framework for incorporating SPHA effects into EARs that builds upon recent advances introducing N into estimates of extinction. By accounting for effects that modify N, our framework explains extinction debt and reduces the uncertainty associated with future estimates of extinction through carefully qualifying the spatial and temporal context of predictions. extinctions are accelerating as humans appropriate ever greater proportions of the earth's habitats (Myers 1989; MEA 2005). Policies seeking to halt or slow extinctions through conservation are controversial because they challenge the dominant contemporary economic paradigm, powerful vested development interests, and embedded norms of human enterprise and consumption (e. g. , Parenteau 1998). It is therefore important for ecological science to provide policy with reliable predictions of the rates at which species extinctions will occur, and how conservation policies and actions will alter species persistence. However, the question of how best to estimate rates of extinction remains unresolved. Traditional approaches for estimating extinction have used the species–area relationship (SAR), which describes the number of unique species that accumulate as a power of increasing area (Rosenzweig 1995). The reverse of the power-law SAR, i. e. , the backward SAR, has often been used to predict the numbers of unique species that will be lost as habitat area is increasingly eroded from a landscape but it can overestimate extinction compared with observed rates (Pimm & Askins 1995; Brooks et al. 1997, 1999). A prevailing explanation for this discrepancy is that there is a time lag before extinction reaches species that survive habitat loss with small and fragmented populations (Heywood et al. 1994; Brooks et al. 1999). The difference between instantaneous and future extinction has been termed “extinction debt” (Tilman et al. 1994). [SEP] Justify:

Output: The text corroborates the claim by discussing how habitat loss, which can be caused by deforestation, leads to extinction. It mentions the necessity of reliable estimates of extinction rates based on habitat area and population size, emphasizing the importance of understanding how species loss is related to habitat degradation. Furthermore, it highlights that extinctions are accelerating as humans appropriate more habitats, reinforcing the connection between deforestation and species extinction.


Input: Task: pass the claim using the given text. Claim: Currently, cryonics is primarily experimental and is not yet proven to revive a preserved body. [SEP] Text: Home Vol 13, No 6 (June 01, 2023) Schmorl’s node of primarily developmental cause and Schmorl’s node of primarily acquired cause: two related yet differen. . . Schmorl’s node of primarily developmental cause and Schmorl’s node of primarily acquired cause: two related yet different entities Letter to the Editor Schmorl’s node of primarily developmental cause and Schmorl’s node of primarily acquired cause: two related yet different entities Yì Xiáng J. Wáng^ Department of Imaging and Interventional Radiology, Faculty of Medicine, University of ^ORCID: 0000-0001-5697-0717. Correspondence to: Dr. Yì Xiáng J. Wáng. Department of Imaging and Interventional Radiology, University of. Email: yixiang_wang@cuhk. edu. hk. Keywords: Spine; Schmorl’s node; radiograph; developmental cause; acquired cause 01, 2023. Accepted for publication Apr 04, 2023. Published online Apr 12, 2023. doi: 10. 21037/qims-23-252 According to the original definition, Schmorl’s node (SN) corresponds histologically to nucleus pulposus herniation into the vertebral spongy bone with thickened trabeculae around the formed node (1,2). Very conflicting literature on the epidemiology of SN have been reported. Several earlier reports noted that, except for the early childhood period, SN prevalence among age groups remains stable (3-6). Dar et al. (4) studied skeleton vertebrae from a normal adult population and noted that SN was more common in men than in women, but SN was age independent. Hilton et al. (5) found no relationship between age and SN with their study of cadaveric spines and thus proposed a developmental pathogenesis for SN. Chen et al. (7) reported that aging was related to greater odds of endplate lesions; however, the prevalence of focal endplate defects remained stable. Sonne-Holm et al. (6) analysed lateral spine radiographs in an adult Caucasian population cohort and did not note any significant correlation between SN and gender, or age. [SEP] Justify:

Output: The text is irrelevant to the claim as it discusses Schmorl's node, its causes, and epidemiology, without mentioning cryonics or any related topics. Therefore, it does not provide any supporting or contrasting evidence regarding the claim about cryonics.


Input: Task: pass the claim using the given text. Claim: Every ancient civilization has left behind detailed written records. [SEP] Text: , the 120x20 goal was devised against the backdrop of more than 230 million women with unmet need) and in interpreting the results. The paper is fundamentally asking about the impact of the FP2020 initiative, but there is no counterfactual or contextual information about what differential mCPR growth looked like prior to FP2020, nor a recognition of the limitation of comparing two-point estimates, especially among sometimes small sub-groups. FP2020 shifted our field to track progress using model-based estimates from FPET to overcome limitations of tracking changes between two surveys. Did the authors consider a modified FPET to see to what degree different sub-groups in countries followed or outperformed the pre-FP2020 trajectories that would have been expected? The question of whether some women (e. g. , the poor or those with no education) are systematically left behind is different from questions of equity. The question of how to define and measure equity in the context of FP programs is one the field continues to struggle with. I am not convinced that the authors’ definition of “equitable” gains as those that are equal to or larger among a more “disadvantaged” group suffices, as this implies an underlying goal of having consistent levels or contraceptive use across all sub-groups/dimensions of equity (regardless of demand). Likewise, is it “equitable” if any groups show slower growth or declines in MCP (as we see evidence from this analysis with some more advantaged groups)? And given starting differential in MCP across sub-groups in many countries, might we expect growth to be slower or faster depending on their placement along the s-curve? While this paper cannot answer those or all questions around the definition of equity in FP programming, it can be clearer about when it is commenting about MCP gains among groups that are generally disadvantaged with FP outcomes (e. g. , the poor, less educated, youth) versus the more elusive concept of equity. The utility of using the Index in place of the country-specific wealth measures (e. g. , DHS quintiles) is not clear to me, given that countries are the unit of analysis. [SEP] Justify:

Output: The text is irrelevant to the claim because it discusses issues related to family planning initiatives and methodologies for measuring equity in various demographic groups. It does not address anything related to ancient civilizations or their written records.


Input: Task: corroborate the claim using the given text. Claim: Deforestation contributes to habitat loss and species extinction. [SEP] Text: Finally, for each site, we plotted the theoretical EAR: (1) without SPHA effects (Equation (4)); and (2) with the effect of SPHA scenario 1 (Equation (5)). We only present results from random sampling and not a theoretical expectation for SPHA scenario 2; its mathematical incorporation into an EAR is relatively intractable because it assumes that species are not distributed at random, i. e. , variation in distances among individuals. EAR underestimates extinction in the presence of SPHA effects when it is assumed that extinction occurs when the last individual of a species dies. Differences in predicted species loss between the theoretical-derived EAR with and without SPHA scenario 1, which assumed that species required a minimum population size of two individuals to persist, were greatest between 25% and 90% habitat loss (gray vs. green lines; Figure 1). SPHA scenarios also predict greater species loss than the EAR without SPHA effects (gray lines beneath overlapping colored regions; Figure 1). Although the backward SAR based on the power-law lacks a theoretical basis for estimating extinction because of habitat loss, its predictions are surprisingly similar to the EAR that incorporates SPHA effects (Figure 1). Figure 1Open in figure viewerPowerPoint Species– and endemics–area curves for five mapped forest plots (Table S1). Dots represent species accumulation within contiguous grid cells 25 m × 25 m; solid and dashed black lines are forward and backward maximum-likelihood fit of the power-law SAR. The gray line is random placement EAR without SPHA effects (Equation (4)), whereas the green line considers SPHA scenario 1 (extinction = <2 individuals; Equation (5)). Shaded green and blue regions are observed ranges for 50 samples of random habitat loss under SPHA scenarios 1 and 2 (extinction = pair-wise distances among individuals of a species >100 m), respectively. Discussion SPHA effects are pervasive in ecological systems (Shaffer 1981; Lande 1988, 1993; Andrén 1997; Hubbell 2001; Laurance 2008), and our results show that failure to incorporate them into the EAR leads to underestimates of future extinction. We also demonstrate that incorporating SPHA effects into the EAR explains the lag between instantaneous and future extinction from habitat loss (Simberloff 1992; Hanski & Ovaskainen 2002; Bulman et al. 2007). [SEP] Justify:

Output: The text corroborates the claim by discussing how habitat loss leads to underestimates of future extinction rates when SPHA (Species Population Habitat Area) effects are not incorporated into ecological assessments. It highlights that greater habitat loss results in greater species loss, as shown by the differences in predicted species loss under varying habitat loss scenarios. This implies a direct link between habitat loss, which occurs due to deforestation, and increased risk of species extinction.


Input: Task: contrast the claim using the given text. Claim: Most biodegradable plastics require industrial composting facilities to break down fully. [SEP] Text: During the intensive rotting phase in all containers maximum temperatures exceeded 75°C with a cooling till the container opening. However, at the end of the intensive rotting the temperatures remained above 65°. The temperature development in containers 1, 3 and 4 was quite similar, in container 2 temperatures were around 5° higher. The temperatures in the post rotting weeks 3–5 varied strongly between 22 and 70°, indicating inhomogeneity in the composting process. After week 4 the temperature increased partially in the specifically dry nets after moistening. However, generally a tendency of cooling was detected with temperatures between 42 and 56° at the end of the composting time of 6 weeks. These high temperatures show that the material was still active, but suitable rotting degrees for marketing of the compost were reached. The inhomogeneity of the temperatures and the wide range of composting conditions in one net is shown in Figure 11. Formation of inhomogeneities initiates early due to the heterogeneous nature of the decaying material, and it progresses during composting as a result of diverse degradation processes stemming from material disparities. Additionally, varying water content levels arise due to aeration via unevenly distributed airflow, further increasing the inhomogeneities. Figure 11 Figure 11. Examples for the surface temperature distribution in the nets before placement in a container (left) and after removal from a container (right). 4. 2 Determination of BDP bag decomposition 4. 2. 1 Remaining BDP macrop12. Mass share of cleaned macrop13. Area number of pre-cleaned BDP macrop4. 2. 1. 1 Impact of washing Washing of pre-cleaned macrop4. 2. 1. 2 Remaining BDP macrop0. 1%). However, the parallel nets show larger remains. In conclusion, a complete decomposition was not achieved for either bag type. For TPS-blend bags a decomposition with only minimal visual residues seems in principle possible, but it requires stringent, homogeneous conditions, which may be challenging to replicate at practical scales without substantial effort. 4. 2. 1. 3 Remaining BDP macrop3. 3. 3 Area number determination of remaining BDP macrop13. 12 with the mass-related determination and Figure 13 with the area-related determination, the same trend is obvious. Considering the large efforts needed for washing, the area number has advantages in the simplicity of the method. [SEP] Justify:

Output: The text contrasts the claim by stating that complete decomposition was not achieved for either bag type, indicating that the composting conditions may not suffice for full breakdown. It mentions that 'only minimal visual residues' seem possible under stringent, homogeneous conditions, which suggests that such conditions—likely found in industrial facilities—are crucial for effective biodegradation. This implies that without these facilities, full breakdown of biodegradable plastics may not occur.


Input: Task: pass the claim using the given text. Claim: Every ancient civilization has left behind detailed written records. [SEP] Text: The shifts in population composition with the IWI measure seems more relevant for examining the relationship between absolute levels of wealth and contraceptive use or for understanding compositional influences on changes in MCP, but not necessarily for analyzing whether within each country women who are relatively poorer or wealthier appeared to be disadvantaged by policies related to the FP2020 goal. find this analysis interesting, I don’t think it is necessary or that it strengthens the findings. It appears that a handful of other long-term FP2020 commitment countries have DHS surveys that have two surveys between 2010 and 2019 were not included (Benin, Cameroon, Guinea and Mozambique, to name a few). If the inclusion criteria are more selective than mentioned (e. g. , if one survey has to be prior to 2012), that should be specified. Alternatively, if some eligible countries were overlooked for this analysis, including them would make the findings more robust. 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. 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. [SEP] Justify:

Output: The text is irrelevant to the claim as it discusses modern survey data and policies related to family planning and demographic changes, without mentioning ancient civilizations or their records.


Input: Task: corroborate the claim using the given text. Claim: Deforestation contributes to habitat loss and species extinction. [SEP] Text: Although the random placement method that links sampling theory to species distributions is a theoretical advance on traditional power-law approaches for predicting extinction, incorporation of SPHA effects into an EAR produces similar predictions of future extinction to those derived from a backward power-law SAR. We emphasize that this finding is entirely coincidental and should not be taken as support for the backward power-law SAR method, which clearly lacks any theoretical basis and should not be used in predicting extinction (He & Hubbell 2011). However, it cannot be automatically assumed that all previous studies have overestimated future extinction by reversing the power-law SAR (e. g. , Pimm & Askins 1995; Brooks & Balmford 1996; Brooks et al. 1997, 1999), contrary to the claim by He & Hubbell (2011) that SARs “always” overestimate extinction. Fragmentation elevates extinction of small populations at intermediate habitat loss Our finding that in the presence of SPHA effects more extinction arises at intermediate habitat loss (i. e. , 25–90%) than predicted by the EAR without SPHA effects (e. g. , He & Hubbell 2011) is consistent with known effects of fragmentation. Increasing habitat fragmentation creates habitat islands that are progressively smaller and more distant from mainland source populations, ultimately reducing population sizes of species (after MacArthur & Wilson 1967). For the simple case of no SPHA effects, the probability of extinction (pi) of a single species i with loss of habitat of area a is equal to the EAR in Equation (3). The change in pi as habitat area is proportionally lost, defined by is then Because the slope of the EAR, i. e. , dpi/dh, depends on Ni and h, reductions in Ni that arise from habitat loss will lead to relatively larger slopes at all but the largest values of h, causing pi to increase more rapidly when relatively less area is lost (Figure 2). Conversely, in larger populations, slopes will be less than 1 and approach zero at all but the highest levels of habitat loss, so pi will increase rapidly only where h is large (Figure 2). The EAR without SPHA effects, however, ignores how habitat loss affects population size, i. e. , Ni is independent of h, and so underestimates extinction of rare species at intermediate h. Our results do demonstrate an increase in pi compared with the EAR without SPHA effects at between ca. [SEP] Justify:

Output: The text corroborates the claim by discussing how increasing habitat fragmentation due to habitat loss creates smaller and more distant habitat islands, which ultimately reduces population sizes of species and increases their risk of extinction. The findings related to fragmentation and its effects on extinction rates demonstrate a clear relationship between habitat loss and its contribution to species extinction.


Input: Task: contrast the claim using the given text. Claim: Most biodegradable plastics require industrial composting facilities to break down fully. [SEP] Text: 1 million tonnes of bioplastics produced in 2020), starch-based materials, including blends (18. 7 %), PBAT and blends (13. 5 %); poly(hydroxyalkanoate) (PHA) (1. 7 %) is expected to strongly develop. 1 Considering waste disposal options, drop-in polymers do not differ from their petro-derived counterparts. Therefore, a sustainable strategy for their end of life is recycling through the existing recycling streams, or, less sustainable, incineration or landfill. In contrast, biodegradable polymers, regardless of their sources, have a larger spectrum of different end-of-life options. They are collected in Figure 2 and are characterized by a level of sustainability that tends to decrease from left to right (i. e. , from reuse, recycling, recovery, to disposal) according to the waste hierarchy principles. Figure 2Open in figure viewerPowerof the end-of-life options for biodegradable plastics. In order to better understand the different scenarios described in Figure 2, it is necessary to make some clarifications and indicate some definitions, with specific attention to the concepts of biodegradability, compostability, and recycling/upcycling. The concept of biodegradability, used to classify bioplastics in Figure 1, refers to a process of plastic decomposition thanks to the action of naturally occurring microorganisms, such as fungi, algae, and bacteria. It is a two-step process that consists of a first fragmentation of the long polymer chains into oligomers and monomers, and, then, in their mineralization by microorganisms forming carbon dioxide, methane, water, and biomass. 2 This process can take place everywhere, for example, in soil, water, or physiological conditions, and is affected by a series of factors, from the chemical nature of the polymers to the availability of oxygen and light, pH temperature, humidity, microorganisms, and enzymes. The same polymer can have different rates of biodegradation under different environments, and, for these reasons, the standards for biodegradable plastics and the testing methodologies are complex and not universally identical. The most broadly recognized biodegradable standards are reported in Table 1. 3, 4 Table 1. Relevant standards for biodegradable plastics. [SEP] Justify:

Output: The text contrasts the claim by explaining that biodegradable polymers have a larger spectrum of different end-of-life options compared to traditional plastics. It indicates that biodegradable plastics can decompose through natural processes by microorganisms and can break down in various environments, not strictly requiring industrial composting facilities. In fact, it mentions that biodegradation can occur in places such as soil and water, thus challenging the idea that full breakdown necessitates industrial composting.


Input: Task: pass the claim using the given text. Claim: Every ancient civilization has left behind detailed written records. [SEP] Text: 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? Interests: No competing interests were disclosed. Reviewer Expertise: 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. . 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: 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. [SEP] Justify:

Output: The text is irrelevant to the claim regarding ancient civilizations and their written records. Instead, it discusses modern issues related to family planning and specific findings related to FP2020, which do not address the history or existence of written records from ancient civilizations.


Input: Task: corroborate the claim using the given text. Claim: Deforestation contributes to habitat loss and species extinction. [SEP] Text: 25% and 90% habitat loss as lending support to the argument that smaller populations have a greater probability of extinction as habitat loss fragments a landscape into progressively smaller increments (Laurance 2008). Figure 2Open in figure viewerPowerof increasing habitat loss on species extinction. (A) EAR for one species i without SPHA effects when population size (Ni) varies from 1 to 100. For the single-species case, the EAR (Equation (4)) corresponds to the probability of extinction pi. (B) Change in the probability of extinction with habitat loss, equal to the slope dpi/dh in (A). Increasing habitat loss that simultaneously reduces Ni will change the slope of the plotted curves; arrow in (A) shows direction of change in curves with decreasing Ni. in (B) causes pi with habitat loss (h) to increase: (1) faster when little area in the landscape is destroyed (small values of h, positive arrow) and (2) slower when most of the landscape is lost (large values of h, negative arrow). dpi/dh estimated for species with Ni of 1, 5, or 10; Ni= 100 omitted for clarity. Although our example shows the greatest variation in extinction occurs from Ni= 1–5 (Figure 2), Ni implicitly represents relative population size (Nr,i), and so will vary with assumptions of the number of individuals required to commit a species to extinction. For example, characteristics of each species i reproductive potential, such as sex ratios (Ri), age-specific fecundity (Fi), and propagule pressure from the surrounding landscape (Pi), along with their respective effects α, β, and γ, may be linear predictors of Nr,i, such that By substituting Ni for Nr,i in (Figure 2), variation in extinction may arise over much larger absolute population sizes than 1–5 individuals. Placing the EAR into spatial and temporal contexts An EAR excluding SPHA effects is misleading because it captures only instantaneous and not eventual (i. e. , future) extinction, thereby ignoring the spatial and temporal contexts that influence species’ persistence. Specifically, instantaneous extinction underestimates future extinction because it excludes species that are committed to extinction while immigration and extinction rates reach a new equilibrium state (Rosenzweig 1995). [SEP] Justify:

Output: The text corroborates the claim by discussing how habitat loss, which is directly associated with deforestation, increases the probability of species extinction. It specifically mentions that 'habitat loss fragments a landscape,' leading to smaller populations, which in turn have 'greater probability of extinction'. Furthermore, the analysis highlights that increasing habitat loss not only affects the population size but also alters the likelihood of extinction, thereby supporting the connection between deforestation, habitat loss, and species extinction.


Input: Task: contrast the claim using the given text. Claim: Most biodegradable plastics require industrial composting facilities to break down fully. [SEP] Text: [3,4][a] Biodegradation environment EN 17033 : 2018 Biodegradable mulch films for use in agriculture and horticulture – requirements and test methods. Biodegradation in soil CEN/TR 17219 : 2018 Biodegradable thermoplastic mulch films for use in agriculture and horticulture. Guide for the quantification of alteration of films. ISO 23517 : 2021 Soil biodegradable materials for mulch films for use in agriculture and horticulture – requirements and test methods regarding biodegradation, ecotoxicity and control of constituents. ISO 14852 : 2018 Determination of the ultimate aerobic biodegradability of plastic materials in an aqueous medium Biodegradation in aqueous medium ASTM D6691-17 Test method for determining aerobic biodegradation of plastic materials in the marine environment. ISO 23977-1 : 2020 ISO 23977-2 : 2020 Plastics: determination of the aerobic biodegradation of plastic materials exposed to seawater – part 1 and 2. Biodegradation in marine environment ISO 22404 : 2019 Plastics: determination of the aerobic biodegradation of non-floating materials exposed to marine sediment. EN 13432 : 2000 Requirements for packaging to be considered recoverable through composting and biodegradation. Industrial composting EN 14995 : 2006 Evaluation of compostability of plastics. ISO17088 : 2021 Specifications for compostable plastics. AS4736 : 2006 Biodegradable plastics suitable for composting and other microbial treatment. ASTM D6400 Labeling of plastics designed to be aerobically composted in municipal or industrial facilities. AS 5810-2010 Biodegradable plastics suitable for home composting. Home composting NF T51-800 Specifications for plastics suitable for home composting. [a] EN standards refers to Europe, ASTM to United States, AS to Australia, NFT to France, ISO standards have a global character. Biodegradability is properly exploitable in applications in which the material biodegrades after it has fulfilled its role in the same site where it was used. In particular, biodegradable plastics can be conveniently used as agricultural mulch films and vegetation mat and could include materials for fishing nets and gears. [SEP] Justify:

Output: The text contrasts the claim by detailing various standards and methods regarding the biodegradation of plastics in different environments, including both industrial composting and conditions suitable for home composting. It highlights that not all biodegradable plastics require industrial composting, as some are suitable for home composting as stated in AS 5810-2010 and NF T51-800. Moreover, it implies that biodegradable plastics can be effectively utilized in contexts other than industrial facilities, such as agricultural applications.


Input: Task: pass the claim using the given text. Claim: Every ancient civilization has left behind detailed written records. [SEP] Text: 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. 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? [SEP] Justify:

Output: The text is irrelevant to the claim as it discusses policy implementation, family planning strategies in Malawi, and feedback on data analysis without mentioning ancient civilizations or written records at all.


Input: Task: corroborate the claim using the given text. Claim: Deforestation contributes to habitat loss and species extinction. [SEP] Text: Our framework advances the work of He & Hubbell (2011) that links sampling theory to species’ distributions by also demonstrating how the EAR can explicitly incorporate spatial and temporal context into predictions of species loss that account for future species loss. The EAR and SAR fundamentally depend on the size of species’ populations (Ni), so modifications of these relationships that allow Ni to vary in specific contexts will offer better predictions of species loss than those derived simply from considering instantaneous extinction. The EAR framework can readily incorporate spatial context to better predict extinction rates. Specifically, we can assume that species’ population sizes Ni are a direct function of habitat area, whereby the population size of species i follows a power function with the area of a landscape after habitat destruction (A–a) (6) where αi and βi are estimated coefficients. The EAR is then: This formulation also allows us to consider how spatial processes, such as composition of the matrix surrounding habitat patches, nonrandom habitat loss, edge effects, and patch isolation, can accelerate extinction (Seabloom et al. 2002; Laurance 2008; Koh & Ghazoul 2010). For example, if A is the total area of a landscape, and is equal to the sum of the individual areas of H habitats (), then Ni can be expressed for each species i as a function of the favorability (γk) and amount of area lost (ak) of each habitat type k: The EAR can then be rewritten as: Such an approach allows the EAR to be extended beyond estimates of extinction arising from the conversion of habitat into inhospitable matrices to predict how particular land-use changes and conservation initiatives will influence species loss (e. g. , Koh & Ghazoul 2010). Predictions of extinction from the backward SAR also have no theoretical basis for incorporating the timescale over which species will be lost, but the EAR again allows this to be estimated explicitly. Returning to the example of the EAR in the absence of SPHA effects, Equation (6) can be modified to express the size of species’ populations (Ni) as a function of time t in addition to remaining habitat. If we assume, e. g. [SEP] Justify:

Output: The text corroborates the claim by discussing the relationship between habitat area and species population sizes. It states that modifications to the relationships of the EAR can offer better predictions of species loss, linking this loss directly to habitat destruction. Specifically, it explains that species population sizes (Ni) are a function of habitat area after habitat destruction, indicating that as habitat is lost, the population sizes of species decrease, which directly supports the claim about deforestation leading to habitat loss and species extinction.


Input: Task: contrast the claim using the given text. Claim: Most biodegradable plastics require industrial composting facilities to break down fully. [SEP] Text: 42-44 Moreover, there is the potential to transform lactate esters into lactide, which could then be converted into PLA, resulting in a circular economy. 45 A different approach aims at partially degrading the macromolecular structure, obtaining oligomers for specific applications. A remarkable example is the fabrication of bio-based adhesives derived from partially depolymerized PLA. 46 2. 2 Starch-based materials 2. 2. 1 Composting Starch-based materials were first developed in the 1970s. 47 In particular, thermoplastic starch (TPS) polymers were produced from starch through the structural modification occurring inside the starch granule when processed at temperature in the presence of specific plasticizers (e. g. , water, glycerol). Literature reports examples of good compostability of starch. For example, 100 % of corn starch at 58 °C was mineralized after 44 days of incubation under aerobic conditions. 48 Effects of concentration were reported by German et al. :49 based on both lab and in-situ experiments, the authors concluded that starch degradation rate decreased by up to 50 % when the starch was <10 % of the soil organic matter. This was attributed to a decrease in enzymatic activity, since the cost for microorganisms to produce extracellular enzymes would be too high compared to the metabolic energy yield when a small amount of starch is available. Torres et al. 50 reported the degradation of 12 starch films from different crops in organic compost, with 50 % of moisture to enable aerobic conditions, and pH range 7. 0–8. 0. The first stage of degradation, mainly associated with the leaching of plasticizer, corresponded to a weight loss of around 30 % in 24 h. The second stage, mainly due to the biological activity and the glycosidic bonds scission, was slower, resulting in a gradual decrease of weight, until 90 % of the original weight in around 20 days. Then, the rate of degradation decreased dramatically, but in 10 days 95 % of weight loss was achieved. Literature reports also examples of effective biodegradation of different starch-based TPS films and foams. 51-53 2. 2. 2 examples of recycling are reported, just related to starch-based blends. Lactic acid can be produced by fungus R. Orizae NRRL395 from powder. 54 Moreover, can be recycled into the same product. [SEP] Justify:

Output: The text contrasts the claim by providing evidence that certain biodegradable materials, specifically starch-based materials, have been reported to biodegrade effectively in various composting conditions without necessarily needing industrial facilities. For example, it cites that 100% of corn starch was mineralized after 44 days under aerobic conditions, indicating that conditions outside of industrial composting can facilitate biodegradation. Additionally, it discusses the stages of degradation in starch films and foams, emphasizing that they can achieve significant weight loss and measure degradation effectively, further supporting the idea that not all biodegradable plastics require industrial composting.


Input: Task: pass the claim using the given text. 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. [SEP] Justify:

Output: The text is irrelevant to the claim as it discusses the assessment of family planning commitments and inequities in countries, without any mention of ancient civilizations or their written records. Therefore, it does not support or contradict the claim in any way.


Input: Task: corroborate the claim using the given text. Claim: Deforestation contributes to habitat loss and species extinction. [SEP] Text: , that Ni increases linearly as a function of t for each species i, such that and αi and βi are estimated coefficients, then the EAR will be: Models from population ecology and conservation genetics of how Ni varies with t and a can provide estimates of αi and βi, enabling the EAR to provide more realistic predictions of timescales of extinction arising from habitat loss. Policy implications of predicting extinction with SPHA effects Estimates of species extinction enter a contested political context (Parenteau 1998), and vested interests may exploit scientific uncertainty to stall and prevent implementation of controversial policies, such as those related to biodiversity conservation (Oreskes & Conway 2010). He & Hubbell (2011) asserted that the backward SAR based on the power-law “always” overestimates extinction from habitat destruction, casting doubt on previous estimates. Here, we show that performance of the backward SAR depends on the temporal context of predictions, which is not always explicitly identified. Our findings agree that the backward power-law SAR overestimates instantaneous extinction, but show that its alternative, a random placement EAR, poorly estimates future extinction unless it is modified to incorporate the ecological effects that commit species to extinction in SPHA. The random placement model does, however, provide a robust framework for incorporating SPHA effects, allowing distinction of instantaneous and future extinction. Temporally and spatially explicit predictions of extinction derived from the EAR that incorporates SPHA effects are ultimately needed to guide conservation policy. Adding SPHA effects to the random placement EAR also reveals approaches for minimizing extinction debt in response to habitat loss. Specifically, the model demonstrates that population sizes within remaining fragments, in addition to habitat area, influence whether a species is committed to extinction. Interventions that increase species’ populations will thus complement interventions focused on habitat area, e. g. , protection and restoration (Kuussaari et al. 2009), thereby reducing future extinctions. of extinction may harm biodiversity by understating the need for, and urgency of, conservation intervention, whereas overestimates may brand scientists as alarmists. Our results demonstrate that the EAR provides a robust foundation for estimating extinction, but that it will underestimate future extinction unless it is modified to incorporate the ecological effects that commit species to extinction in small populations and/or small areas of habitat. [SEP] Justify:

Output: The text corroborates the claim by discussing the ecological effects of habitat loss on species extinction. It emphasizes that models estimating extinction rates should incorporate ecological factors, revealing that population sizes and remaining habitat areas influence whether species are committed to extinction. Furthermore, it highlights that interventions aimed at increasing species populations in addition to focusing on habitat area are essential for reducing future extinctions, thus connecting habitat loss directly to species extinction.