Input: Task: corroborate the claim using the given text. Claim: Poaching poses a major threat to endangered species like elephants. [SEP] Text: Figures AbstractSelective harvest, such as poaching, impacts group-living animals directly through mortality of individuals with desirable traits, and indirectly by altering the structure of their social networks. Understanding the relationship between disturbance-induced, structural network changes and group performance in wild animals remains an outstanding problem. To address this problem, we evaluated the immediate effect of disturbance on group sociality in African savanna elephants—an example, group-living species threatened by poaching. Drawing on static association data from ten free-ranging groups, we constructed one empirically based, population-wide network and 100 virtual networks; performed a series of experiments ‘poaching’ the oldest, socially central or random individuals; and quantified the immediate change in the theoretical indices of network connectivity and efficiency of social diffusion. Although the social networks never broke down, targeted elimination of the socially central conspecifics, regardless of age, decreased network connectivity and efficiency. These findings hint at the need to further study resilience by modeling network reorganization and interaction-mediated socioecological learning, empirical data permitting. The main contribution of our work is in quantifying connectivity together with global efficiency in multiple social networks that feature the sociodemographic diversity likely found in wild elephant populations. The basic design of our simulation makes it adaptable for hypothesis testing about the consequences of anthropogenic disturbance or lethal management on social interactions in a variety of group-living species with limited, real-world data. Author summary We consider the immediate response of animal groups to human disturbance by using the African savanna elephant as an example of a group-living species threatened by poaching. Previous research in one elephant population showed that poaching-induced mortality reduced social interaction among distantly related elephants, but not among close kin. Whether this type of resilience indicates that affected populations operate similarly before and after poaching is an outstanding problem. Understanding this is important because poaching often targets the largest or most socially and ecologically experienced group members. Drawing on empirical association data, we simulated poaching in one empirically based and 100 virtual elephant populations and eliminated the most senior or sociable members. Targeted poaching of sociable conspecifics was more impactful. Although it did not lead to population breakdown, it hampered theoretical features of intraspecific associations that in other systems have been linked with social cohesion and the efficiency of transferring socially valuable information. Our findings suggest that further inquiry into the relationship between resilience to poaching and group performance is warranted. [SEP] Justify:

Output: The text corroborates the claim by discussing how poaching impacts group-living animals, specifically mentioning African savanna elephants, which are threatened by poaching. The passage describes the consequences of poaching on social networks amongst elephant populations and indicates that targeted poaching of socially central individuals decreases network connectivity and efficiency, thus supporting the assertion that poaching is a significant threat to these endangered species.


Input: Task: contrast the claim using the given text. Claim: All carbohydrates cause weight gain. [SEP] Text: 568] for all-cause mortality and 0. 431 [0. 215−0. 867] for cancer-related mortality). In addition, these findings were consistent in the BMI < 25 kg/m2 population after stratifying according to BMI. Weight gain reduced all-cause mortality and was marginally associated with cancer-related mortality in the entire population (HRs [95% CIs]: 0. 149 [0. 044−0. 505] for all-cause mortality and 0. 289 [0. 080−1. 045] for cancer-related mortality). Weight gain decreased the risk for all-cause mortality in the BMI < 25 kg/m2 population (0. 119 [0. 027−0. 533]). These findings emphasize the importance of maintaining or gaining body weight after initial diagnosis of cancer. Obesity is closely related to poor prognosis in multiple cancer types. Obesity induces various metabolic dysfunctions and inflammatory processes that increase insulin, insulin-like growth factor, leptin, and interleukin-6, while decreasing adiponectin. These disarrangements activate intracellular signaling through Janus kinase pathway signal transducers and activators of transcription and mitogen-activated protein kinase and phosphatidylinositol 3-kinase pathways, which are frequently dysregulated in carcinogenesis. [26] In addition, adipose tissue produces aromatase that converts androgen to estrogen, which potentiates estrogen signaling and leads to sex hormone-dependent cancers such as breast and ovarian cancer. [27,28] Thus, intentional weight reduction decreased obesity-related cancer incidence. [29,30] Obesity or weight gain cause poor health outcomes in long-term cancer survivors through the development of second primary cancer, recurrence, and cardiovascular diseases. [31–33] Conversely, underweight or weight loss increases the risk of mortality in the advanced cancer population. Weight loss is one of the most common manifestations of cancer. In particular, cancer cachexia, accompanied by a catabolic state and malnutrition, is a devastating and frequently irreversible condition that affects 50% to 80% of advanced cancer patients. [34] Weight loss, including that associated with cancer cachexia, significantly increases cancer mortality. Therefore, weight loss may affect health outcomes according to cancer stage and patient adiposity in different ways. [SEP] Justify:

Output: The text contrasts the claim by discussing the complex relationship between weight gain and health outcomes, particularly in the context of cancer. It emphasizes that obesity is related to poor prognosis and cancer, while weight loss and underweight status are associated with increased mortality. This implies that not all weight gain—and by extension, not all carbohydrates—necessarily leads to negative health outcomes; rather, the context of obesity and its consequences play a more significant role.


Input: Task: pass the claim using the given text. Claim: Adaptive radiation explains species diversification in new environments. [SEP] Text: Further studies are required to measure the extant of ongoing hybrid speciation, for example in A. leucokranos. There, field observations coupled with experiments will allow to identify the conditions in which hybrids have a better fitness than their parents, illustrating the thight relationship linking species ecology and evolutionary processes. MethodsPhylogenetic reconstructionWe used previously extracted DNA from 41 individuals (see [19] for details; Additional file 3: Table S1) representing 27 species of clownfish to analyse the evolutionary history of mitochondrial genes. We amplified parts of the ATP86, CytB and 16S markers via polymerase chain reaction (PCR) with a 25 μl reaction mixture containing ~50 ng of DNA template, 2. 5 μL GoTaq buffer, 3 μL dNTPs (2. 5 μM), 1 MgCl2 (25 μM), 1 μL of both forward and reverse primer and 0. 3 μL of Taq polymerase (). Primer sequences and PCR cycles were set as in [24] for ATP86 and CytB, and [25] for the 16S. We purified the amplification products with the (Qiagen, GmbH, Germany). We sequenced the purified products forward and reverse strands with the 3. 1 Terminator cycle sequencing kit (), according to the manufacturer’s instructions, and separated the products on an ABI Prism 3100 genetic analyser (). We assembled a nuclear dataset from sequences generated in a previous study [19]; Additional file 3: Table S1). The nuclear dataset is 6,679 base pairs long and comports seven genes (BMP4, Glyt, Hox6, RAG1, S7, Svep, Zic1). We used MAFFT 6. 864b [36] with default settings to align each mitochondrial and nuclear gene individually. We verified each alignment visually and concatenated the mitochondrial and nuclear datasets in two separate super-matrices with SequenceMatrix [37]. We estimated the mitochondrial and nuclear phylogenetic relationships of clownfish species with MrBayes 3. 2. 1 [38]. The parameters of the nucleotide substitution process for each gene in the mitochondrial and nuclear data sets were sampled across the GTR model space during the Bayesian MCMC [39]. This approach has the advantage of removing the need of a priori testing for a specific model of substitution (e. g. [40]). [SEP] Justify:

Output: The text is irrelevant to the claim as it focuses on methodological details regarding phylogenetic research and hybrid speciation without addressing adaptive radiation or its role in species diversification in new environments.


Input: Task: corroborate the claim using the given text. Claim: Poaching poses a major threat to endangered species like elephants. [SEP] Text: In addition, our simulation approach offers a generalizable basis for hypothesis testing in other social species, wild or captive, subject to exploitation by humans. Citation: Wiśniewska M, Puga- (2022) Simulated poaching affects global connectivity and efficiency in social networks of African savanna elephants—An exemplar of how human disturbance impacts group-living species. PLoS 18(1): e1009792. Yamir Moreno, University of Zaragoza: Universidad de : April 5, 2021; Accepted: December 23, 2021; Published: January 18, 2022Copyright: © 2022 Wiśniewska et al. This is an open access 10. 5061/dryad. g4f4qrfrz. Funding: M. W. received funding for this project through the 2018-2019. The website for this award is The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Competing interests: The authors have declared that no competing interests exist. IntroductionIn group-living animals, from insects to mammals [1,2], interactions among conspecifics with diverse social roles [3–5] impact individual survival [6–9], reproductive success [10–12] and adaptive behaviors [13–16]. In species with complex organization characterized by flexible aggregates of stable social units [17–19], the loss of influential group members through natural or anthropogenic causes can be detrimental to surviving conspecifics [20–22] and to entire populations [23,24]. Unlike natural phenomena, such as fire [25,26], harvest is intrinsically nonrandom [27–29]. For instance, poachers profiting from pet trade prefer to capture immature individuals as the most economically desirable commodity [30], eliminating gregarious ‘brokers’ who engage in frequent or diverse social interactions [31,32]. As another example, trophy hunters target individuals with prominent features, such as elephants with big tusks [33,34], killing the oldest and socioecologically experienced conspecifics [35–39]. Animal social network analysis, which quantifies intraspecific relationships as ‘networks of nonrandomly linked nodes’, is useful in demonstrating how elimination of individuals with key social roles impacts closely knit animal groups [40,41]. [SEP] Justify:

Output: The text corroborates the claim by detailing how poaching negatively affects the social structures and populations of elephants. It explains that poachers target influential group members, such as older elephants with big tusks, which can severely disrupt the social network and survival of the species. This aligns with the assertion that poaching is a significant threat to endangered species like elephants, emphasizing its detrimental impact on both individual animals and their groups.


Input: Task: contrast the claim using the given text. Claim: All carbohydrates cause weight gain. [SEP] Text: 84) from young to late adulthood, and 1. 20 (1. 09 to 1. 32) from middle to late adulthood. Maximum overweight had a very modest or null association with mortality across adulthood. No significant associations were found between various weight change patterns and cancer mortality. obesity across adulthood, weight gain from young to middle adulthood, and weight loss from middle to late adulthood were associated with increased risks of mortality. The findings imply that maintaining normal weight across adulthood, especially preventing weight gain in early adulthood, is important for preventing premature deaths in later life. IntroductionObesity is a major global public health problem. The global prevalence of obesity in adults increased from 3% in 1975 to 11% in 2016 among men and from 6% to 15% among women. In the US, the prevalence of obesity in adults was 36% for men and 38% for women in 2016 compared with 11% for men and 14% for women in 1975. 1 shaped or J shaped relation between body mass index (BMI) and mortality has been well established. 23 However, many previous cohort studies included only a single measurement of BMI, which ignored the dynamic feature of body weight over time. Thus more studies are needed to assess the long term consequences of weight change during certain life periods. A recent meta-analysis of 26 prospective studies in participants aged 40 to 65 years at baseline reported that both weight loss and weight gain from middle adulthood to old age were related to elevated mortality risk. 4 Another meta-analysis of 17 prospective studies in adults aged 60 years or older reached similar conclusions. 5 However, adults gain weight more rapidly from young to middle adulthood, and excess adiposity mostly accrues in this period compared with the period from middle to late adulthood when weight begins to stabilise or even decrease. 6 In addition, preventing weight gain from young to middle adulthood might be more important than promoting weight loss, because achieving long term weight loss and maintaining it are difficult once a person becomes obese. 7 Evaluating the long term effect of weight change, particularly weight gain from young to middle adulthood, on future health is thus important. Although some previous cohort studies reported that weight gain from young adulthood to either midlife or late adulthood was associated with increased mortality risk,891011 the results were not entirely consistent, with some studies reporting no significant association. 1213 Some studies found that weight loss was associated with increased mortality risk,121415 whereas others did not. [SEP] Justify:

Output: The text contrasts the claim by discussing obesity and weight gain dynamics across different life stages. It specifies that weight gain occurs more rapidly from young to middle adulthood and emphasizes the need for preventing weight gain in early adulthood rather than suggesting that all carbohydrates lead to weight gain. Furthermore, the mention of studies indicating no consistent significant associations between weight gain and mortality challenges the absolutist claim about carbohydrates contributing to weight gain.


Input: Task: pass the claim using the given text. Claim: Adaptive radiation explains species diversification in new environments. [SEP] Text: We performed, for each dataset, two independent runs of MrBayes with four parallel MCMC chains, each 10 million generations long, and sampled model parameters every 1000 generations. We checked for optimal parameter convergence using the ‘sump’ command and by visualising the trace files and the ESS values of the MCMC chains using Tracer v 1. 5 [41]. After the removal of 25% of the trees as burn-in, we merged the two independent runs to generate a majority-rule consensus tree for both mitochondrial and nuclear dataset that included all compatible groups. Hybrid signalWe assessed cytonuclear discordance by comparing visually the topology of both consensus phylogenetic trees. This step was facilitated by the use of the ”cophyloplot” function available in the R package Ape [42]. We further applied the framework of the HET on the nuclear dataset only [6]. Hybrid taxa are intermediate to the parental species when considering their nuclear genome, but they share identical alleles at each individual locus with only one parent [43]. When included in a phylogenetic tree based on a matrix of concatenated nuclear markers, a hybrid taxon will introduce an excess of homoplasy due to the conflicting phylogenetic signal present in the corresponding gene tree topologies in the clades containing the two parental species. Thus, the removal of a putative hybrid should reduce conflicts in the phylogenetic tree and result in increased support values for the nodes that includes the parental species [6]. While AFLP have initially been proposed as input data for the HET, it is conceptually similar to use the alignments of several nuclear genes. The only drawback of using sequence data is a reduction in power due to the lower amount of data and less independence between sites. Yet, by increasing the number of genes studied, this should not be a major issue. We implemented this test in R 3. 0. 1 [44] and used RAxML 7. 3. 5 [45] to perform the phylogenetic inference and bootstrap support (BS) using the ‘’ model of nucleotide substitution and specified a different partition for each gene in the dataset. For a species i, we first removed it from the complete concatenated alignment of nuclear data. We used this reduced data set lacking species i to build a phylogenetic tree and estimate node support with 100 bootstrap replicates. [SEP] Justify:

Output: The text provided does not address the claim regarding adaptive radiation and species diversification. Instead, it discusses methods for phylogenetic inference and the assessment of hybrid taxa without referencing adaptive radiation or environments. Therefore, it is irrelevant to the claim.


Input: Task: corroborate the claim using the given text. Claim: Poaching poses a major threat to endangered species like elephants. [SEP] Text: For example, node deletion experiments manipulating empirical association data have revealed that while some disturbed groups fracture into multiple components [42,43] others stay connected [44]. In biological populations, elimination of impactful group members through harvest, is much less destabilizing to persistence of larger social groups compared to small ones [20]. Our current understanding of whether the relationships in remaining groups, or group fragments, operate as prior to disturbance is based on a small number of studies. In an instance of captive zebra finches, group foraging ability decreased following repeated social disturbance [45]. In simulated primate groups, network disturbance led to a decrease in its global connectivity and the efficiency of social diffusion indices, but did not lead to group fragmentation [46]. These indices depend on network structure; are based on an assumption that transmissible currency, such as information, diffuses through network links [47]; and have been related to cohesion, the transfer of social currency and robustness to loss of influential conspecifics [48–50]. In light of the anthropogenic impact on animal communities [51–54], evaluating the relationship between post-disturbance social structure and resilience vis-à-vis group performance in natural animal systems is becoming increasingly important [20,55]. To explore this relationship, we considered the African savanna elephant (Loxodonta africana)—a group-living species threatened by poaching [56–58]. Elephant social organization consists of several tiers, ranging from transitional clans and bonded groups of distant and intermediate kin, to matrilineal core units of adults and their immature offspring [59]; or flexible groups of postdispersal males of varying ages and kinship [36]. While immature elephants frequently engage in affiliative interactions [60,61], mature individuals are not only well socially connected but also more experienced about resource distribution and phenology [62,63], and about social dynamics [64–66]. The interactions among individuals with diverse social roles across social tiers manifests as fission-fusion dynamics in response to changing sociophysical landscape [19,67]. Poaching—which during the militarized wave of the past decade eliminated large subsets of populations including mature and immature elephants [68]—impacts demography [69], resource acquisition [70,71] population genetics [72] and various social behaviors [73,74] in targeted populations. [SEP] Justify:

Output: The text corroborates the claim by specifically stating that poaching 'which during the militarized wave of the past decade eliminated large subsets of populations including mature and immature elephants,' clearly indicating that poaching has a significant detrimental impact on elephant populations and therefore supports the assertion that it poses a major threat to this endangered species.


Input: Task: contrast the claim using the given text. Claim: All carbohydrates cause weight gain. [SEP] Text: 5 kg to 20 kg) or weight gain from non-obese to obese BMI was not significantly associated with mortality risk. Therefore, the results were overall consistent with the previous studies. 4Our study has the unique feature of examining the weight change patterns across adulthood and mortality risk in later life. We found that the relations of stable obesity and weight gain from non-obese to obese BMI with mortality were generally stronger from young to middle adulthood than from middle to late adulthood. Weight gain in adults mostly occurs from young to middle adulthood, but studies in this critical period are still lacking. 35 A study in 1657 Finnish men with mean baseline age of 47 years reported that mortality risk was significantly increased in the highest quarter of weight gain (≥15. 0 kg) from age 25 years to baseline compared with the lowest quarter. 8 In the Cohort study with 56 868 US participants aged 40-65 at baseline, Hirko et al reported that being obese at 21 years old only or in both young and middle adulthood was significantly associated with higher mortality risk, but weight gain from non-obesity to obesity was not. 15 The reasons for the inconsistent results might be that this study used stable non-obesity as the reference group and most of the participants were black Americans, in whom the authors previously reported that obesity in mid to late adulthood was not associated with higher mortality risk. 36 Using data from the of Health-AARP cohort with 109 947 never smokers aged 50-71 years at entry, Adams et al found that weight gain was positively related to mortality, with stronger associations for weight gain from age 18 to 35 years and from 35 to 50 years than from age 50 to 69 years. 10 Institutes of Health-AARP study also found that weight loss in late adulthood, but not in early adulthood, was significantly associated with increased mortality risk. Our results are consistent with these studies and indicate that avoiding obesity at young age and preventing weight gain from young to middle adulthood could be an important strategy to reduce future mortality risk. Several studies have also investigated the relation of weight change from young to late adulthood and mortality risk, but the results were not entirely consistent. Some studies found that weight gain over this period was associated with increased risk of all cause mortality,91011 whereas other studies reported that weight loss, but not weight gain, was related to increased mortality risk,1237 which was similar to our results. [SEP] Justify:

Output: The text contrasts the claim by discussing the complex relationships between weight gain, obesity, and mortality risk, but it does not directly support the assertion that all carbohydrates are responsible for weight gain. Instead, it emphasizes the importance of avoiding obesity and weight gain in certain life stages while citing studies that show inconsistent results regarding weight gain and its association with mortality, which suggests that not all weight gain is linked to carbohydrate consumption.


Input: Task: pass the claim using the given text. Claim: Adaptive radiation explains species diversification in new environments. [SEP] Text: Second, we generated a null distribution of BS for each node of the consensus phylogenetic tree by removing at random a species j that is different from the focal species i, and inferred, again, the phylogenetic tree and BS. This was replicated 100 times. Third, we compared the BS for each node obtained by the reduced dataset lacking the focal species i to those of the null distribution. We identified outlier values of BS when the BS of a node fell above the highest value still within 1. 5 interquartile range of the upper quartile of the null distribution [16],[46]. This represent a case where the focal species i is of hybrid origin which has the effect of reducing drastically the BS of the node ancestral to the parental species. Finally, this process was carried on for each taxon included in the phylogeny. At first, we performed this analysis using single species removals, but then extended the framework to monophyletic pairs, triplets and so on, of species (n up to 8) to account for hybrid species which may have already further diversified into several descendants. Each time, we removed n random species from the dataset and generated a new null distribution of BS where n random species were removed from the alignment. Molecular cloning of recent hybridsWe obtained, through an aquarium fish importer, samples from three unidentified clownfish specimens that displayed hybrid characteristics such as aberrant colouration or shape. Hybrid 1 and 3 were collected in Bali, Indonesia, while hybrid 2 originated from Guinea. We followed the protocol described above to sequence, for each new sample, all three mitochondrial markers and the nuclear gene BMP4. We further isolated from those three individuals and a sample of A. leucokranos (a species that may have been described form hybrid individuals [20]), putative parental sequences of BMP4 using molecular cloning. We cloned the purified PCR products of the BMP4 gene into the pTZ57R/T vector using the InsT/(Fermentas, Vilnius, Lithuania). Then, we amplified up to 12 clones for each individual with the M13 forward and reverse primers to ensure that we sequenced all existing variants. We purified and sequenced the PCR products as above. We ensured, by checking visually all chromatograms, that no sequence showed double peaks, which would indicate heterozygous sites and thus a failure of the cloning procedure. [SEP] Justify:

Output: The text provides a detailed description of a scientific methodology involving phylogenetic analysis and molecular cloning of hybrid species. However, it does not address the concept of adaptive radiation or provide any evidence or discussion on how such processes relate to species diversification in new environments. Therefore, the text is irrelevant to the claim.


Input: Task: corroborate the claim using the given text. Claim: Poaching poses a major threat to endangered species like elephants. [SEP] Text: Evidence from social network analysis using data spanning periods of low and high poaching in one free-ranging population revealed that the composition and association patterns within matrilines were conserved among close but not distant surviving kin. This outcome suggests clan-level impact of poaching on network structure and resilience, with little detrimental effect at the bonded group- or core unit-levels [75]. Whether changes in network structure in elephants relate to group functionality is difficult to test directly. However, quantifying network connectivity together with global efficiency while simulating poaching may shed new light on the theoretical capacity for dissemination of social currency and the limitation to social resilience in disturbed populations. These insights may eventually inform our understanding about the mechanisms of group performance, and means of mitigating human-elephant conflict [76,77] to conserve this economically important but endangered, keystone species [78,79]. We characterized the immediate effect of eliminating the most influential individuals on the global structure of simulated, social networks. We used a static set of empirical association data on one free-ranging elephant population from Park (NP) in Kenya [80] because continuous data featuring network reorganization after poaching, necessary to parametrize time-varying models, do not yet exist for wild elephants. Initially, we assembled one, empirically based social network using the Amboseli dataset and conducted a series of ‘poaching’ experiments by either incrementally removing 1) the oldest elephants as presumably the most experienced and prone to poaching, or topologically central individuals with high betweenness centrality (often referred to as social hubs) as the most sociable network members [81,82]; or 2) by removing individuals randomly [43,83]. To quantify network-wide structural changes, we evaluated four theoretical indices: two of which are used to diagnose network-wide connectivity (i. e. , clustering coefficient and modularity, dependent on local neighborliness or global partitioning, respectively); and the other two are commonly used to express the efficiency of social diffusion (i. e. , diameter and global efficiency, based on the distance or pervasiveness of diffusion, respectively) [49]. To set these results in the context of a large-scale variation in demography and social interactions found in real elephant populations, we generated 100 distinct, virtual populations modeled on demographic trends in empirical data. [SEP] Justify:

Output: The text corroborates the claim by discussing the impact of poaching on elephant populations, specifically highlighting how social network analysis shows changes in the composition and association patterns within matrilines due to poaching. This suggests a clan-level impact on network structure and resilience, indicating that poaching affects the survival and social dynamics of these endangered animals, thus affirming the claim that poaching poses a major threat to elephants.


Input: Task: contrast the claim using the given text. Claim: All carbohydrates cause weight gain. [SEP] Text: The inconsistency might be due to the differences in sample size (ranging from 2512 to 118 140) and substantial variations in the definitions of weight change across studies, which make direct comparisons difficult. In addition, the baseline age varied in different studies and previous studies showed that the obesity-mortality association tended to decline with increasing age. 3839 As also shown in our study, the association between weight gain and mortality attenuated as people got older, whereas the association with weight loss became stronger and significant in middle to late adulthood. In this study, we found that both weight gain from non-obesity in young adulthood to obesity in middle adulthood and weight loss from obesity in middle adulthood to non-obesity in late adulthood were associated with higher risk of heart disease mortality. The results were consistent with some previous studies of cardiovascular disease mortality. 1140 Weight change patterns were not significantly associated with cancer mortality across adulthood in our study, but we did not have data on incident cancer or site specific cancer mortality, so more studies are still needed to examine the relations between weight change and cancer risk. In our study, maximum overweight was generally not significantly related to mortality risk. This weight change pattern consisted of three heterogeneous groups, and the results should be interpreted cautiously. The positive relations of stable overweight and normal to overweight patterns with mortality were attenuated or even reversed with increasing age, which was consistent with our main recommendation of preventing weight gain at an early age. Weight loss from overweight to normal weight was consistently associated with higher risk of mortality across adulthood, and more studies are needed to confirm the results in other populations and explore the potential effect of weight loss among overweight people. Strengths and limitations of studyThis study had several strengths including its large and nationally representative sample, high follow-up rate, and detailed analysis of weight change from young adulthood through midlife to late adulthood. Our study shows the importance of examining the weight change patterns in different life periods given that people are more likely to gain weight and accumulate weight rapidly from young to middle adulthood, whereas weight begins to stabilise or even decrease from middle to late adulthood. 6 Furthermore, weight gain from young to middle adulthood mostly reflects accumulation of fat mass, whereas weight loss in middle and late adulthood is usually accompanied by comorbidities and a decrease in lean mass and an increase in fat mass,738 so the underlying mechanisms of the harmful effect of weight change in certain life periods might differ. [SEP] Justify:

Output: The text contrasts the claim by discussing weight change patterns and their associations with various health outcomes, including mortality. It emphasizes that weight gain varies with age and is not solely attributable to carbohydrate consumption. Additionally, the text suggests that weight gain and weight loss have different associations with health risks, indicating the complexity of weight change rather than a simple cause-and-effect relationship tied to carbohydrates alone.


Input: Task: pass the claim using the given text. Claim: Adaptive radiation explains species diversification in new environments. [SEP] Text: We assembled identical clones in Geneious 6 (Biomatters), expecting to recover two different sequences (one for each parent) if the individual is truly a hybrid, or only one if it is not the case. We aligned the mitochondrial and nuclear sequences of the hybrid individuals to the two super-matrices with MAFFT [36]. Finally, we expected clones to cluster with the sequences of their parental species. We identified the putative parents of the individuals by reconstructing the phylogenetic trees of both super-matrices using MrBayes 3. 2. 1 in the same manner as described above. All newly generated sequences have been deposited in the EMBL database (accession numbers in Additional file 3). Availability of supporting dataDNA sequences are deposited in GenBank under the accession numbers found in Additional file 3. Multiple sequences alignments as well as phylogenetic trees are available in TreeBase, informationGL is a PhD student in the group of NS. NS is a Professor at the University of Lausanne. NS research group focuses on a variety of organisms and questions with a particular interest on understanding the drivers of adaptation both at the levels of the genes or genomes but also through the modelling of the evolution of the phenotypes and the ecological niche of species. Additional files 67. 10. 1086/430331. 7. 10. 1073/pnas. 242585899. 2863. 10. 1111/mec. 12083. 206. 10. 1093/molbev/msr183. 207. 10. 1016/j. tree. 2004. 01. 003. 246. 10. 1111/j. 1420-9101. 2012. 02599. x. 281. 10. 1111/jeb. 12026. 737. 10. 1126/science. 1157966. 315. 10. 1007/s11692-012-9209-0. 97. 10. 1111/j. 1558-5646. 2008. 00599. x. 35. 10. 1046/j. 1365-294X. 2003. 01803. x. 451. 10. 1046/j. 1365-2540. 2000. 00680. x. 62. 10. 1073/pnas. 95. 20. 11757. 4398. 10. 1098/rspb. 2012. 1667. 10. [SEP] Justify:

Output: The text is irrelevant to the claim regarding adaptive radiation and species diversification. It mainly discusses methodologies for sequence alignment and phylogenetic analysis without addressing the concept of adaptive radiation or its role in species diversification.


Input: Task: corroborate the claim using the given text. Claim: Poaching poses a major threat to endangered species like elephants. [SEP] Text: For instance, applied without consideration for social interactions, trophy hunting of pride lions may intensify infanticide by immigrant males [23,28,123] and displace distressed females to hunt in fringe habitats exacerbating conflict with humans [124,126]. Prior to making decisions about lethal management or translocations of ‘problem’ individuals, wildlife managers may be well served by simulating relevant disturbance on focal populations, quantifying social network effects and adjusting management decisions for better outcomes [41,127]. As another example, the use of social network analysis in captive animal populations is already helping researchers characterize the dynamics of harmful agonistic interactions, such as tail biting in newly mixed groups of domestic pigs [128]. These data may help parametrize simulated disturbance to social network structure in captive systems by taking into account traits such as genetic relatedness in group composition and its link to aggression and health of animal subjects. Insights from this type of assessment may, in turn, improve animal welfare and safety of farm workers [129,130]. In summary, our work confirms previous findings that although elimination of the most central network members in elephant populations decreases network connectivity at the population level, it does not lead to network fragmentation—at least in networks with the structure and at the level of simulated disturbance tested in this research. Uniquely, however, our research shows that poaching-like stress in a large number of virtual elephant populations impedes the theoretical efficiency of social diffusion. A follow-up question about the relationship between the structural network changes and population performance will require simulating a dynamic process that accounts for network reorganization after poaching. In addition, to tease apart an individual’s importance due to network position versus age-specific experience will require a method that accounts for interaction-mediated information transfer. Still, our simulation approach can be easily altered to test basic hypotheses about disturbance of social interactions in wild and captive systems. Supporting informationS1 Table. The composition of 100 virtual population according to kinship. Detailed here are the number of clan, bond and core groups, as well as individuals per population; the number of bond and core groups, and individuals per clan; the number of core groups per group; and the number of individuals per bond and core groups. [SEP] Justify:

Output: The text corroborates the claim by discussing the impact of poaching-like stress on virtual elephant populations. It states that while the elimination of key members in elephant networks decreases connectivity, it does not cause fragmentation. However, the research indicates that poaching-like stress hampers social diffusion in these populations, implying that poaching poses significant risks to the social structures of elephants, thus threatening their survival.


Input: Task: contrast the claim using the given text. Claim: All carbohydrates cause weight gain. [SEP] Text: Another strength of our research is that we adjusted for a large number of potential confounders, including socioeconomic status and lifestyle factors. However, some factors, such as physical activity, diet quality, and self reported health status at baseline, could also be mediators for the relations of weight status and weight change patterns in young and middle adulthood with mortality risk, because they could be influenced by weight status and weight changes in young adulthood. 414243Our study also has several limitations. Firstly, our approximation of middle adulthood (age range 30-80 years, interquartile range 36-56) overlapped with late adulthood (age range 40-90, interquartile range 46-66). However, in the analysis stratified by baseline age, the results remained and were even stronger in participants under 60 years old at baseline, which further confirmed that weight gain and stable obesity in younger adulthood were associated with higher mortality risk. Secondly, we used recalled and self reported weight data at age 25 years and 10 years before the baseline survey and thus misclassification bias may have been introduced. However, several validation studies and a recent meta-analysis showed that recalled early life weight could be a valid measure to use in life course epidemiological analysis. 44 Thirdly, many covariates were available only at baseline, so we could not use time varying covariates to capture changes in possible confounders over time. Fourthly, we could not differentiate intentional from unintentional weight change, and additional information on reasons of weight change may enable better interpretation of the results of future studies and thus appropriate intervention strategies. Lastly, we did not evaluate the relations of changes in other adiposity related markers such as waist circumference and fat mass with mortality owing to lack of data at different time points. Further studies with repeated data on these markers may provide a more comprehensive picture of the changes in obesity status and mortality risk. Conclusions and public health implicationsOur study found that stable obesity across adulthood and weight gain from young to middle adulthood was associated with increased risks of all cause and heart disease mortality, as was weight loss in middle to late adulthood. Future studies are needed to unravel the mechanisms underlying the association between weight change across adulthood and mortality, particularly the relations of changes in body composition to mortality. In addition, as weight loss is less achievable (only 1. 4% participants changed from the obese to the non-obese category from young to late adulthood), our results suggest that prevention of weight gain might be more important. [SEP] Justify:

Output: The text contrasts the claim by discussing factors associated with weight gain, such as obesity and weight change patterns, without specifically stating that all carbohydrates cause weight gain. It emphasizes that weight gain is influenced by a variety of factors and suggests that prevention of weight gain is more critical than attributing it solely to carbohydrate intake.


Input: Task: pass the claim using the given text. Claim: Adaptive radiation explains species diversification in new environments. [SEP] Text: 1186/1471-2148-12-212. 2149. 10. 1111/jbi. 12370. 598. 10. 1098/rspb. 2006. 3758. 2562. 10. 1111/j. 1420-9101. 2011. 02391. x. 113. 10. 1086/668599. 88. 10. 1016/S1055-7903(03)00278-1. 16. 10. 1016/j. ympev. 2008. 12. 010. 276. 10. 1016/j. ympev. 2008. 04. 024. 27. 10. 1016/j. gene. 2006. 03. 028. 146. 10. 1038/424145a. 831. 10. 1046/j. 1365-2656. 2002. 00649. x. 369. 10. 1007/s00338-010-0713-3. 347. 10. 1007/s10641-010-9606-0. 353. 10. 1007/BF00001464. 138. 147. 10. 1016/j. tree. 2006. 11. 002. 22. 10. 1111/j. 1365-294X. 2011. 05433. x. 3066. 10. 1093/nar/gkf436. 180. 10. 1111/j. 1096-0031. 2010. 00329. x. 3. 2: efficient Bayesian phylogenetic inference and model choice across a large model space. Syst Biol. 2012, 61: 539-42. 10. 1093/sysbio/sys029. 33. 10. 1093/molbev/msh123. 10. 1038/nmeth. 2109. 10. 1186/1471-2148-7-214. 290. 10. 1093/bioinformatics/btg412. 9. 10. 1046/j. 1365-294X. 2002. 01550. x. 90. 10. 1093/bioinformatics/btl446. 10. 1186/1742-9994-1-5. 4. 0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. waiver ( applies to the data made available in this 10. [SEP] Justify:

Output: The text does not provide any information related to adaptive radiation or species diversification. It primarily comprises a sequence of DOIs and publication references without context or content relevant to the claim.


Input: Task: corroborate the claim using the given text. Claim: Poaching poses a major threat to endangered species like elephants. [SEP] Text: Experimental disturbances reveal group-level costs of social instability. Sci. 2018;285. pmid:30429300 View 46. Puga-. Social style and resilience of macaques’ networks, a theoretical investigation. Primates. 2019;60: 233–246. View 47. . Detecting and quantifying social transmission using network-based diffusion analysis. J Anim Ecol. 2020. View 48. . Transmission in Animals: Lessons from Studies of Diffusion. Front Psychol. 2016;7: 1147. View 49. Pasquaretta C, Levé M, Claidière N, van de Social networks in primates: smart and tolerant species have more efficient networks. Sci Rep. 2014;4: 7600. View 50. Sosa S, Sueur C, Puga-Gonzalez I. Network measures in animal social network analysis: Their strengths, limits, interpretations and uses. Evol. 2020. View 51. ôrtes. Decay of interspecific avian flock networks along a disturbance gradient in Amazonia. Sci. 2014;281: 20132599. View 52. . Human disturbance causes widespread disruption of animal movement. Evol. 2021. View 53. -C. Mammal diversity will take millions of years to recover from the current biodiversity crisis. . 2018;115: 11262–11267. View 54. Approaching a state shift in Earth’s biosphere. Nature. 2012;486: 52–58. View 55. . Intense harvesting of eastern wolves facilitated hybridization with coyotes. Ecol Evol. 2012;2: 19–33. View 56. é Continent-wide survey reveals massive decline in African savannah elephants. PeerJ. 2016;4: e2354. View 57. Blanc J. Loxodonta africana. of Threatened Species. In: of [Internet]. 2008 [cited 28 Aug 2019]. 58. -. Illegal killing for ivory drives global decline in African elephants. . 2014;111: 13117–13121. View 59. Wittemyer G, Douglas-Hamilton I, Getz WM. The socioecology of elephants: analysis of the processes creating multitiered social structures. Anim Behav. 2005;69: 1357–1371. View 60. . African elephant play, competence and social complexity. [SEP] Justify:

Output: The text provides evidence supporting the claim that poaching is a significant threat to endangered elephants. Notably, it mentions that illegal killing for ivory is a major driver of the global decline in African elephants. This indicates that poaching directly contributes to the endangerment of the species, thereby corroborating the claim.


Input: Task: contrast the claim using the given text. Claim: All carbohydrates cause weight gain. [SEP] Text: Taken together, the findings indicate that maintaining normal weight throughout the adulthood, especially prevention of weight gain in early adulthood, should be encouraged to reduce risk of premature deaths. Finally, further studies are still needed to consider other health related and obesity related outcomes, and clinical trials on the long term health consequences of weight loss are also warranted. What is already known on this topicHigh body mass index in adulthood is associated with higher risk of premature deathScientific evidence on weight change from young to late adulthood or from middle to late adulthood in relation to risk of mortality is not entirely consistentLittle is known about associations between weight change across adulthood, especially from young to middle adulthood, and all cause and cause specific mortalityWhat this study addsWeight gain from young to middle adulthood was associated with increased risk of mortality from all causes and heart diseases in US adultsWeight loss over this period was not significantly related to mortality, and people who remained obese had the highest risk of mortalityAcross adulthood, the association between weight gain and mortality attenuated with increasing age, whereas that with weight loss from middle to late adulthood became stronger and significantThe results highlight the importance of maintaining normal weight across adulthood, especially preventing weight gain in early adulthood, for preventing premature deaths in later lifeFootnotesContributors: CC, XFP, and AP conceived the study design. CC and YY did the statistical analysis. CC and AP wrote the manuscript. All authors provided critical revisions of the draft and approved the submitted draft. The corresponding author attests that all listed authors meet authorship criteria and that no others meeting the criteria have been omitted. AP is the guarantor. Funding: This study was supported by grants from the Research and of China to AP (2017YFC0907504) and the (No 176596) and of the Council (No 20180062) to XFP. The funders had no role in design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, and approval of the manuscript; or the decision to submit the manuscript for publication. Competing interests: All authors have completed the ICMJE uniform disclosure form at (available on request from the corresponding author) and declare: no support from any organisation for the submitted work other than those described above; no financial relationships with any organisations that might have an interest in the submitted work in the previous three years; no other relationships or activities that could appear to have influenced the submitted work. [SEP] Justify:

Output: The text contrasts the claim by highlighting that weight gain is specifically associated with weight changes across adulthood, rather than being attributed to all carbohydrates. It emphasizes findings that maintaining normal weight and preventing weight gain, especially in early adulthood, is crucial for reducing risks of premature death. This indicates that weight gain does not solely stem from carbohydrate intake, but rather from overall weight management throughout life.


Input: Task: pass the claim using the given text. Claim: Cognitive biases influence decision-making and perception. [SEP] Text: 1017/S1092852915000681 [Opens in a new window] This is an 4. 0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited Copyright © Press 2015 eating disorder (BED) is the most common of eating disordersReference Hudson, Hiripi, Pope and Kessler 1 and is characterized by excessive and rapid food intake without concomitant purging behaviors. BED is commonly associated with obesity but also occurs without obesity. Reference Hudson, Hiripi, Pope and Kessler 1 Reference Kessler, Berglund and Chiu 2 A range of cognitive abnormalities has been reported in BED. The study of cognitive processes allows us to address several issues of relevance to BED. First, cognitive processes have well-defined neural correlates from animal and human studies and represent powerful intermediate endophenotypes that mediate brain function and behavior. Reference Insel, Voon and Nye 3 Thus, cognitive impairments may reflect underlying impairments in corresponding brain substrates. Second, demonstrating similarities across differing pathological disorders provides insights into dimensional mechanistic similarities that might cut across seemingly differing behaviors and assist with further conceptualization of a disorder. Reference Insel, Cuthbert and Garvey 4 How BED might compare with other eating disorders, obesity without BED, and disorders of addiction or impulse control may help with conceptualization of BED. Reference Gearhardt, White and Potenza 5 – and Fletcher 8 This converges with the trend toward dimensional psychiatryReference Insel, Cuthbert and Garvey 4 by conceptualizing binge eating beyond the simple phenomenon of eating behavior (eg, anorexia nervosa or bulimia nervosa), to identifying biological or cognitive endophenotypes that may link this behavior of persistent, out-of-control, rapid consumption of a highly palatable natural reward (food) with other potentially relevant behaviors. Third, differentiating between BED and non-BED obese subjects can further help with defining subtypes of obesity and help particularly with characterizing the heterogeneity of obesity. Thus, understanding cognitive processes underlying BED may help elucidate underlying neural networks, mechanisms leading to aberrant behaviors, and also help with conceptualization of BED and differentiating BED as a subtype of obesity. Aberrant cognitive processes may also represent a marker as a predictor for outcomes, for treatment targets, and to assess therapeutic outcomes. [SEP] Justify:

Output: The text does not directly address the claim regarding cognitive biases and their influence on decision-making and perception. Instead, it focuses on binge eating disorder (BED) and discusses cognitive processes related to this disorder, specifically how cognitive impairments may relate to brain function, behavior, and the classification of BED among other eating disorders. Thus, it is irrelevant to the claim.


Input: Task: corroborate the claim using the given text. Claim: Poaching poses a major threat to endangered species like elephants. [SEP] Text: pmid:21411454 View 117. van é C. The 2020 elephant die-off in Botswana. PeerJ. 2021;9: e10686. pmid:33510975 View 118. Poaching empties critical wilderness of forest elephants. Curr Biol. 2017;27: R134–R135. pmid:28222286 View 119. . Long-term impacts of poaching on relatedness, stress physiology, and reproductive output of adult female african elephants. Conserv Biol. 2008;22: 1590–1599. pmid:18759771 View 120. . State-space models reveal a continuing elephant poaching problem in most of Africa. Sci Rep. 2020;10: 10166. pmid:32576862 View 121. Mengak MT. Series—Wildlife Translocation. U. S. Department of Agriculture. Animal & 2018. Available: 122. . Giraffe (Giraffa camelopardalis) social networks in areas of contrasting human activity and lion density. McQualter K, editor. Ethology. 2019;125: 702–715. View 123. . Protection from harvesting restores the natural social structure of eastern wolf packs. Biological Conservation. 2010;143: 332–339. View 124. . Shooting pheasants for sport: What does the death of Cecil tell us? Palmer C, editor. People and Nature. 2020;2: 82–95. View 125. . Using multi-scale behavioral investigations to inform wild pig (Sus scrofa) population management. PLoS One. 2020;15: e0228705. pmid:32032396 View 126. . leo Bos taurus Types. Animals (Basel). 2020;10. pmid:32316176 View 127. Shier DM. Effect of family support on the success of translocated black-tailed prairie dogs. Conserv Biol. 2006;20: 1780–1790. pmid:17181813 View 128. Büttner. Social network analysis—centrality parameters and individual network positions of agonistic behavior in pigs over three different age levels. Springerplus. 2015;4: 185. pmid:25932371 View 129. -. One Welfare—a platform for improving human and animal welfare. Vet Rec. 2016;179: 412–413. [SEP] Justify:

Output: The text provides multiple references that highlight the negative impacts of poaching on elephants, specifically mentioning studies that discuss the long-term effects of poaching on African elephants' physiology and reproduction, as well as indicating a persistent problem of elephant poaching across Africa. These elements strongly support the claim that poaching is a significant threat to endangered species such as elephants.


Input: Task: contrast the claim using the given text. Claim: All carbohydrates cause weight gain. [SEP] Text: reports BackgroundThere is ample evidence for the U-shaped or J-shaped relationships between body mass index (BMI) and mortality risk [1, 2]. However, most previous studies ignored the dynamic feature of body weight over time. Many adults may experience weight gain due to a sedentary lifestyle and excessive dietary intake [3]. In contrast, a progressive decrease in weight is often observed later in life [4]. Although the association between weight change and mortality has recently attracted much attention, the findings remain inconclusive. A meta-analysis of 26 prospective studies has shown that both weight gain and loss were associated with increased mortality risk among middle-aged and older adults [5]. In contrast, a longitudinal study in Australia indicated that weight loss, but not weight gain, was associated with increased all-cause and cause-specific mortality among older adults [6]. Previous studies predominantly focused on Western populations and were mostly limited to relatively small sample sizes. Meanwhile, these studies differed substantially, involving inconsistent weight indicators (mostly absolute weight) [7, 8] and variability in the categorization of weight change [6, 7]. Moreover, the threshold of weight loss or weight gain at which the risk of mortality begins to increase remains inadequately delineated. Therefore, a study that encompasses a large-scale community-dwelling population and utilizes an appropriate nonlinear methodology is imperative to understand the association between weight change and mortality risk. Age differences have also been observed in the association between weight change and mortality [7, 8]. A longitudinal study conducted in Korea confirmed the interactive associations between absolute weight loss and mortality among middle-aged and older adults [8]. Using prospective data from two longitudinal cohort studies, Yuan et al. found that absolute weight gain was associated with a higher risk of all-cause mortality among participants aged < 60 years, while this association was not observed among those aged ≥ 60 years [7]. Thus, our analyses were stratified by age. In this large-scale prospective cohort study of nearly 0. 75 million Chinese adults, we evaluated the associations of percentage change in BMI and absolute weight change with mortality from all causes, non-communicable disease, CVD, and cancer. MethodsStudy populationThis prospective cohort study used data from the Cohort (SHBDC) in China. Details of the study design and population have been reported in Additional file 1. In brief, the SHBDC has enrolled participants at any time during 2009–2022 in Shenzhen, China. [SEP] Justify:

Output: The text contrasts the claim by discussing various factors contributing to weight gain and loss, indicating that a sedentary lifestyle and excessive dietary intake are more significant factors than carbohydrate intake alone. Furthermore, it highlights the complexity and variability in weight change, suggesting that not all weight gain is solely due to carbohydrates.


Input: Task: pass the claim using the given text. Claim: Cognitive biases influence decision-making and perception. [SEP] Text: Risk taking can also be considered a form of impulsivity and can occur in the context of risk (or known probability) or uncertainty (in which the probability is unknown). Response inhibition Response inhibition is the capacity to inhibit prepotent motor responses, which can span the processes of action restraint (eg, tested using the “go/no-go” task, in which actions that are not yet initiated are inhibited) or action cancellation (eg, tested using the “stop signal” task, in which actions that are already initiated are inhibited). Reference Dalley, Everitt and Robbins 10 These are common measures of response control, with meta-analyses showing deficits in attention-hyperactivity disorder, a disorder associated with impulse control impairmentsand Schachar 11 substance use disorders, particularly to stimulants, nicotine, and alcohol, but not to opioids or cannabis; and pathological gambling. Reference Smith, Mattick, Jamadar and Iredale 12 Impairments in the stop signal task have also been shown in unaffected siblings of stimulant-dependent subjects, which suggests an endophenotypic risk factor for the development of addiction. and Bullmore 13 Studies comparing obese BED patients against obese controls or against age- and gender-matched, healthy, non-obese controls suggest that response inhibition tested using the go/no-go task or stop signal task are impaired in BED only if paired with food cues. In one study using a go/no-go task with food and body words, BED subjects made more commission errors to both food and body words compared to non-BED obese subjects. Reference Mobbs, Iglesias, Golay and Van der Linden 14 Similarly, another study showed that BED compared to non-BED obese subjects had prolonged stop signal reaction time in a stop signal task involving food images. The study also showed that BED had greater commission errors to food versus non-food images. Reference Svaldi, Naumann, Trentowska and Schmitz 15 In contrast, 2 studies comparing BED versus their own healthy volunteers did not show an impairment in a neutral stop signal task without food cues. [SEP] Justify:

Output: The text does not address the claim regarding cognitive biases; it focuses on different aspects of risk taking, response inhibition, and behavioral disorders without linking these to cognitive biases or their influence on decision-making and perception.


Input: Task: corroborate the claim using the given text. Claim: Poaching poses a major threat to endangered species like elephants. [SEP] Text: Elephant poaching in Niassa Reserve, Mozambique: population impact revealed by combined survey trends for live elephants and carcasses Published online by Press: 15 October 2014 Vernon R. Booth andKevin M. author details Vernon R. Booth* Affiliation: 9. Dunham Affiliation: PO Box CH385, Chisipite, Harare, Zimbabwe * (Corresponding author) E-mail vernonrbooth@gmail. com 0. 87 mb) View PDF [Opens in a new window] Save to to Save to & Permissions [Opens in a new window] in the populations of large herbivores in Niassa Reserve, Mozambique, have been monitored through biennial aerial surveys since 1998. The elephant Loxodonta africana population has been subjected to intensive illegal hunting since 2006. We used a simple population model to mimic the observed trends in the numbers of live and dead elephants to demonstrate the impact of poaching. The number of fresh or recent carcasses recorded was used in the model as an index of the annual mortality rate. A maximum likelihood analysis to compare population models revealed that the best fit to the survey estimates of both live elephants and old or very old carcasses was a model that started with 6,635 elephants in 1987. This number increased through births by 4. 6% annually and decreased through deaths from natural and anthropogenic causes. In the best-fit model, the mean mortality rate in any year was 3. 2 times the observed 1 + 2 carcass ratio (ratio for carcasses in age categories 1 and 2), and carcasses remained visible for a mean of 6 years. The model suggested that c. 900 elephants were poached during 2007–2010 and another c. 1,000 during 2011. Population estimates for live elephants and carcasses are now routine outcomes of aerial surveys conducted as part of the CITES programme for Monitoring the of Elephants, and our method can be applied to any population with a time series of estimates for live and dead elephants. surveycarcasselephantMozambiqueNiassapoachingpopulation modelpopulation trend Issue 1 January 2016 10. [SEP] Justify:

Output: The text corroborates the claim by detailing the impact of elephant poaching in Niassa Reserve, Mozambique, where illegal hunting has significantly affected the population of elephants (Loxodonta africana). It mentions that the population model indicated poaching killed approximately 900 elephants between 2007 and 2010, and another 1,000 in 2011, highlighting that poaching directly threatens the survival of this endangered species.


Input: Task: contrast the claim using the given text. Claim: All carbohydrates cause weight gain. [SEP] Text: Corresponding with our results, two other studies conducted in Western nations similarly observed that weight loss, but not weight gain, was associated with increased all-cause mortality among middle-aged adults [12, 13]. In contrast, several studies with relatively small sample sizes found no significant association between weight loss and mortality, while weight gain was associated with increased mortality [14,15,16]. Two previous longitudinal studies examined the associations of weight change with CVD and cancer mortality, yielding conflicting results [17, 18]. A study conducted among 1664 adults aged ≥ 65 years revealed that weight loss was associated with higher CVD mortality but not cancer mortality [17]. In contrast, the study indicated that self-reported weight loss was associated with higher CVD mortality and cancer mortality among older adults, which is consistent with our findings [18]. Nevertheless, our study showed that excessive increase in BMI was also significantly associated with increased CVD mortality among older adults, while BMI change was not associated with CVD mortality among middle-aged adults. The possible explanation for the inconsistent findings in previous studies, apart from variations in the ages of the study participants [6, 7] and the relatively small sample sizes [14, 15, 17], may be also attributed to variability in the weight indicators [6, 19], different categorizations of weight change [6, 18], use of self-reported weight [18, 20], long duration of changes [20, 21], and the absence of accounting for potential confounding factors, such as baseline BMI [20, 22]. An alternative explanation may be that the results in many cohort studies could be influenced by potential reverse causation bias. For instance, the majority of these studies did not comprehensively exclude individuals with a history of serious illnesses [21, 23, 24]. In our study, we reduce the reverse causation bias by further excluding participants with CVD, cancer, respiratory disease, kidney disease, or digestive disorders. Additionally, we adjusted for baseline BMI to control the impact of confounding, as obese individuals often exhibit weight loss tendencies in contrast to lean individuals, while having a much higher mortality rate. One of the mechanisms by which a decrease in BMI would lead to a significantly higher risk of mortality is through reducing physical capability, impairing cardiopulmonary performance an increased risk of falls, and disability [25]. However, a lesser decrease in BMI was associated with increased mortality risk among older adults, but not middle-aged adults. [SEP] Justify:

Output: The text contrasts the claim by discussing a range of studies that link weight gain to mortality in varied contexts. It does not support the notion that all carbohydrates necessarily cause weight gain; rather, it indicates that associations with weight change and health outcomes are complex and reliant on numerous factors, suggesting that not all weight changes are due to carbohydrate intake, as evidenced by findings related to BMI and various health outcomes.


Input: Task: pass the claim using the given text. Claim: Cognitive biases influence decision-making and perception. [SEP] Text: Reference Wu, Giel and Skunde 16 Reference Mole, Irvine and Worbe 17 In these same studies, although the stop signal task was not impaired in BED subjects, subjects with bulimia nervosa had impaired response inhibition compared to healthy volunteersReference Wu, Giel and Skunde 16 and non-BED obese subjects, and those with alcohol use disorders had impaired response inhibition compared to healthy volunteers. Reference Mole, Irvine and Worbe 17 These studies thus suggest that response inhibition in the context of neutral cues may not be impaired in BED; however, in the context of food (and body) cues, both early and late response inhibition are more impaired in BED relative to non-BED obese subjects. Delay discounting Delay discounting tasks in both animal and human studies involve the selection of an immediate smaller reward and a larger delayed reward with variations in either the delay to the reward or the magnitude of the reward to calculate an indifference point in which the 2 options are selected equally. Reference Dalley, Everitt and Robbins 10 This represents the value attached to the delayed reward. Greater delay discounting is observed in and Rubia 18 and across a range of substance use disorders. Reference Bickel, Koffarnus, Moody and Wilson 19 In studies of BED subjects with mild obesity of mixed gender [body mass index (BMI) 33–35]Reference Mole, Irvine and Worbe 17 to moderate obesity in women (BMI 36–38),Reference Davis, Patte, Curtis and Reid 20 both BED and non-BED obese subjects had greater discounting of delayed rewards compared to healthy volunteers. In contrast, in a study in women with higher BMIs (BMI 42), BED subjects had greater discounting to delayed rewards in multiple domains, including food, money, sedentary activity, and massage time compared to non-BED obese subjects. Reference Manwaring, Green, Myerson, Strube and Wilfley 21 Thus, in the domain of delay discounting, an influence of severity of obesity appears to play a role: greater devaluation of the delayed reward appears to be common across BED and non-BED obese subjects, with mild to moderate BMI levels suggesting a core common cognitive deficit. [SEP] Justify:

Output: The text does not directly address cognitive biases or their influence on decision-making and perception. Instead, it discusses various studies related to response inhibition and delay discounting in individuals with different eating disorders and obesity. While the text mentions decision-making in the context of delay discounting, it does not explicitly connect these concepts to cognitive biases, making the text largely irrelevant to the claim.


Input: Task: corroborate the claim using the given text. Claim: Poaching poses a major threat to endangered species like elephants. [SEP] Text: 1017/S0030605314000568 [Opens in a new window] © Fauna & 2014 have been notable increases in both the poaching of African elephants Loxodonta africana and the illegal trade in ivory since 2007, mainly because of the rising demand for ivory in the fast-growing economies of Asia, particularly China and Thailand (UNEP et al. , 2013). Elephant populations in Eastern and that were regarded as secure are now threatened, as a wave of poaching seems to be spreading east and southwards across Africa. the of Elephants (MIKE) programme (CITES, 2004) collects data on elephant poaching and law enforcement from >50 sites across Africa (Burn et al. , Reference Burn, Underwood and Blanc2011). However, this programme depends on the law enforcement authority at each site collecting and reporting the carcass data used to judge the effectiveness of their law enforcement. Aerial surveys can provide both an independent check and an assessment of elephant population trends over a large area. The MIKE standards for aerial surveys of elephant populations (Craig, Reference Craig2012) require the collection of data on both live elephants and elephant carcasses. Douglas-Hamilton & Hillman (Reference Douglas-Hamilton and Hillman1981) were among the first to draw attention to the importance of carcass number as an indication of the trend in a population of live elephants. Later, Douglas-Hamilton & Burrill (Reference Douglas-Hamilton, Burrill, Kayanja and Edroma1991) showed that the proportion of dead elephants was correlated with the percentage change in the number of live elephants during the previous 4 years. Wells (Reference Wells1989) modelled a theoretical elephant population under different mortality regimes. He suggested that temporal patterns in the number of dead elephants (as a proportion of live plus dead elephants) permitted natural mortality alone to be distinguished from mortality from both hunting and natural causes, and for selective hunting to be distinguished from unselective hunting. Here we describe a method that uses a simple population model to reveal the trend in an elephant population by combining survey estimates for live elephants with survey estimates for elephant carcasses. [SEP] Justify:

Output: The text corroborates the claim by stating there have been notable increases in the poaching of African elephants due to the rising demand for ivory, which highlights the threat posed by poaching to elephant populations. It also mentions that elephant populations previously considered secure are now threatened by poaching, providing direct evidence that supports the claim.


Input: Task: contrast the claim using the given text. Claim: All carbohydrates cause weight gain. [SEP] Text: 48) at both 20 years and entry had a higher mortality rate than women who were underweight/healthy weight at both points. ConclusionsWomen who self-reported overweight and obesity at 20 years had a shorter life expectancy in this cohort of women attending breast cancer screening. Weight gain from 20 years was common in this group. Girls and women should be supported to maintain a healthy weight throughout the lifespan to help increase life expectancy. Trial registration number NCT04359420, retrospectively registered 24/04/2020. reports BackgroundOverweight (body mass index [BMI] 25–29. 9 kg/m2), obesity (BMI ≥ 30 kg/m2) [1] and weight gain increase the risk of multiple diseases in women, including type 2 diabetes, cardiovascular disease (CVD), postmenopausal breast cancer (BC) and 12 other types of cancer [2,3,4]. These diseases all increase risk of mortality [5]. Rates of overweight and obesity for women in England have risen over the past 25 years; currently 60% are overweight including 29% with obesity [6]. BC is the most common cancer in women worldwide [7], and the second highest cause of cancer mortality in UK women [8]. Both the and the for state that weight gain during adulthood, and excess weight throughout adulthood increases risk of postmenopausal BC [7]. Conversely, excess weight between 18 and 30 years is associated with a reduced risk of both pre- and postmenopausal BC [7, 9]. One concern is that the potential benefits of early obesity on BC risk may be interpreted as a positive reinforcement of excess weight amongst younger women. Some studies have shown that higher weight in early adulthood is associated with an increase in all-cause mortality in women [10,11,12]. Using data from the of Screening () study, which recruited women from the in England, we have already shown the association of higher young adulthood weight with increased BC risk. We wished to look at the wider implications of early adulthood weight and weight change within this population of women attending breast screening in the UK. The primary aim of this study was to use data from the cohort to assess all-cause mortality by BMI at 20 years and BMI change between 20 years and entry. We hypothesized that increased BMI at 20 years, and increased weight gain during adulthood would be associated with increased all-cause mortality. [SEP] Justify:

Output: The text contrasts the claim by discussing how weight gain is common in women and the associated risks of being overweight and obese, particularly indicating that weight gain during adulthood increases health risks. It does not imply that carbohydrates specifically cause weight gain, but rather that excess weight from any source contributes to various health issues. Therefore, it undermines the blanket statement made in the claim.


Input: Task: pass the claim using the given text. Claim: Cognitive biases influence decision-making and perception. [SEP] Text: 29 Reference Voon, Irvine and Derbyshire 30 In the task, subjects held down a space bar while performing a serial reaction time task in which they released the space bar to touch the square on the touch screen in which a target appeared. The main outcome was premature responses prior to target onset. In contrast to the BED findings, the same study demonstrated enhanced waiting impulsivity across multiple disorders of substance addiction (abstinent methamphetamine, alcohol-dependent, and cannabis users, and current smokers) and binge drinkers. This study suggests that waiting impulsivity, unlike that observed in disorders of addiction, is not impaired in obese subjects with or without BED. However, in this study, the degree of obesity was mild to moderate, and the task was not tested in the context of food cues or premature responding in BED, both of which may influence outcomes. In a study on reflection impulsivity, which assesses the amount of evidence accumulated prior to a decision, there were no differences between either BED or non-BED obese subjects and healthy volunteers tested using the Task. Reference Mole, Irvine and Worbe 17 The information sampling task involves probabilistic inference, in which subjects are shown 25 squares and must use the accumulated evidence (sequential opening of the square color) to decide whether the squares are predominantly blue or pink. In the Stroop word-color interference task, subjects must report the color in which the word is printed rather than the meaning of the word itself. The task is a complex task that assesses multiple elements, including the capacity to inhibit responding to a conflicting prepotent response, assess conflict, and shift responding. Studies investigating Stroop word-color interference (ie, to non-food related stimuli) report no differences between BED and non-BED obese subjects, suggesting that there is not a fundamental impairment in cognitive control of conflict at least as measured using the Stroop. Reference Duchesne, Mattos and Appolinario 31 Reference Galioto, Spitznagel and Strain 32 In a functional MRI study using the Stroop word-color task, BED subjects had lower activity in regions implicated in self-control, including the ventromedial prefrontal cortex, inferior gyrus, and insula, compared to non-BED obese controls, although no behavioral differences were observed. [SEP] Justify:

Output: The text discusses various studies and tasks related to impulsivity and cognitive control but does not directly address the influence of cognitive biases on decision-making or perception. It focuses more on specific conditions like binge eating disorder (BED) and the outcomes of specific tasks without making a clear connection to cognitive biases.


Input: Task: corroborate the claim using the given text. Claim: Poaching poses a major threat to endangered species like elephants. [SEP] Text: A previous model of an elephant population (Dunham, Reference Dunham2008) is extended, firstly by varying the annual mortality rate in the model to reflect the observed variation in the number of fresh or recent carcasses of elephants, and secondly by mimicking the observed variations in both the number of live elephants and the number of old or very old carcasses. We illustrate the method using long-term aerial survey data for the savannah elephant population in the Reserve in northern Mozambique. population is the largest elephant population in Mozambique and the only one that has been surveyed regularly in recent years. The trend in the estimated number of live elephants in the Reserve has not been clear (Craig, Reference Craig2011), however, with the sample survey estimates suggesting that the number of live elephants increased from c. 12,000 during 2006 to c. 20,000 during 2009, before declining to c. 12,000 during 2011 (Table 1). Real changes of this magnitude over just a few years are unlikely. However, it is not unusual for the trend in population number to be unclear, especially if the population estimates are derived from a relatively small number of sample surveys. We determine the likely trend in the Niassa elephant population by using a model that mimics both the number of live elephants and the number of carcasses. In the process, our analysis reveals the recent impact of illegal hunting on the elephant population. Table 1 Summary of the results of aerial sample surveys of elephants Loxodonta africana and elephant carcasses in Reserve in northern Mozambique (Fig. 1). The carcasses are categorized according to age, as described in the Methods. Study area Reserve (c. 42,000 km2) is in northernmost Mozambique, covering part of Province and nearly one-third of (Fig. 1). It is the country's largest conservation area and the third largest protected area in Africa, and has the highest concentration of wildlife in Mozambique. Tanzania's Reserve (c. 50,000 km2) lies 160 km north of the Rovuma River, which forms the international border as well as the northern border of Reserve. Approximately 9,000 km2 of communal land in southern Tanzania, lying between the Niassa and Selous reserves, is designated the Selous–(Baldus & Hahn, and Hahn2009). Niassa has a tropical climate, with mean monthly temperatures of c. [SEP] Justify:

Output: The text corroborates the claim by detailing the recent impact of illegal hunting on the elephant population in Mozambique. It discusses how variations in the number of fresh carcasses reflect mortality rates within the population, suggesting that illegal activities are contributing to declines in elephant numbers. This aligns with the claim that poaching threatens endangered species like elephants.


Input: Task: contrast the claim using the given text. Claim: All carbohydrates cause weight gain. [SEP] Text: 18, 95% CI: 1. 09–1. 27; HRBecoming underweight = 1. 35, 95% CI: 1. 25–1. 46) and cancer death (HROverweight to normal = 1. 20, 95% CI: 1. 04–1. 39; HRBecoming underweight = 1. 44, 95% CI: 1. 24–1. 67), while stable overweight could increase the risk of total death (HRStable overweight = 1. 11, 95% CI: 1. 05–1. 17) and death from stroke (HRStable overweight = 1. 44, 95% CI: 1. 33–1. 56). Interaction effects were observed between age and weight change on cancer mortality, as well as between baseline BMI and weight change on all-cause, heart disease, and stroke mortality (all Pinteraction <0. 01). Conclusions: Weight loss was associated with an increased risk of all-cause, cancer, and heart disease mortality, whereas excessive weight gain and stable overweight were associated with a higher risk of stroke mortality. Efforts of weight management should be taken to improve health status. Trial registration: NCT00342654. weight is one of the markers of nutritional status. [1] Most of the current studies usually use body mass index (BMI), which is defined as the weight (kg) divided by the square of the height (m2), to assess obesity or low body weight. The association between body weight or BMI and the risk of common chronic diseases has been widely reported. [2–5] Multiple disease states, such as cancer and cardiovascular disease, are associated with weight extremes and unexpected weight changes. [6] Most of the current studies confirmed the J-shaped or U-shaped correlation between BMI and the risk of mortality. [7,8] For example, obesity was confirmed to be related to metabolic and cardiovascular risks,[9] while some studies indicated that mortality in the elderly and chronic disease populations was consistently associated with a lower BMI. [10,11] However, body weight changes continuously throughout a lifetime. Many prospective studies only conducted one-time measurements of weight or BMI, and whether the dynamic weight change is an independent risk factor for cancer, stroke, cardiovascular diseases, or other chronic diseases remains controversial. [SEP] Justify:

Output: The text contrasts the claim by discussing the relationship between body weight, BMI, and various health outcomes, including the risks associated with weight gain and loss. It indicates that excessive weight gain and stable overweight are linked to higher mortality risks, as evidenced by statements about 'stable overweight' being associated with increased risks of total death and stroke mortality. This implies that weight gain, in general, is not solely determined by carbohydrates but is influenced by a variety of factors, and does not support the blanket statement that all carbohydrates cause weight gain.


Input: Task: pass the claim using the given text. Claim: Cognitive biases influence decision-making and perception. [SEP] Text: Impulsivity and compulsivity are believed to be overlapping constructs that might sit at opposite ends of a spectrum: for example, models of addiction posit that impulsivity transitions to compulsivity over the course of addictionReference Dalley, Everitt and Robbins 10 and Volkow 35 they also have overlapping processes and neural substrates, and can co-exist within the same disorder. Compulsivity, similar to impulsivity, also consists of heterogeneous subtypes with discrete but overlapping neural substrates between subtypes and can be either simple or complex. On a simple level, flexibility includes stereotypies, perseveration or impaired switching. On a more complex level, subtypes can include attentional set shifting, reversal, habit, or exploration behaviors as reviewed in the following sections. Set shifting Set shifting assesses a higher order capacity to shift between differing abstract rules or sets. There are several tasks that measure set shifting. In the Sorting Task, subjects must match cards to 1 of 4 cards, which differ by specific dimensions (color, shape, or number) based on specific rules that change over time. In the Test (TMT), Trail B, which tests the capacity to alternate between numbers and letters, subjects draw must draw a line to connect a series of numbers and letters in order. A meta-analysis investigating set shifting across multiple task types in 3 different eating disorder populations (BED, anorexia nervosa, and bulimia nervosa) identified impaired set shifting with a small to moderate effect size across all 3 populations (BED effect size: g=−0. 53). and Friederich 36 A moderate effect size was shown in studies of obesity (g=−0. 61) but not in overweight studies (g=−0. 07). The meta-analysis included only 2 BED studies with a total of 53 BED subjects. Further analysis of the 2 studies and other recently published studies suggests there may be differences between BED and obesity as a function of BMI. In one study with mild obesity (BMI 31–32) assessing the TMT, Trail B, processing time was impaired in BED compared to non-BED obese subjects. [SEP] Justify:

Output: The text does not address cognitive biases or their influence on decision-making and perception. Instead, it focuses on impulsivity, compulsivity, and their related constructs in the context of addiction and set-shifting tasks, which is tangential to the claim about cognitive biases.


Input: Task: corroborate the claim using the given text. Claim: Poaching poses a major threat to endangered species like elephants. [SEP] Text: Data for 2000–2011 were provided by the MODIS burnt area product (no MODIS data are available for 1998). The percentage of area burnt was also recorded during aerial surveys of wildlife during 2002–2009. Blank cells indicate the absence of data. of increased mortality of elephants Increased mortality of African elephants and a subsequent population die-off often follow severe drought, as observed, for example, in Tsavo (Kenya) during 1970–1971 (Corfield, Reference Corfield1973). However, annual rainfall in Niassa was average or above-average after 2006 (Table 2), which suggests that the observed increase in mortality during that period was not drought-related. We considered the possibility that interannual variation in the percentage of the Reserve that was burnt influenced the visibility of elephant carcasses to aerial observers, but the increase in the number of carcasses recorded during 2011 could not be explained by an increase in the proportion of the Reserve that was burnt (Table 3). We believe that there is no natural explanation for the increased mortality observed after the 2006 survey but that it resulted from illegal hunting. Hence, it is likely that the additional 1,901 elephants that the models suggest died during 2007–2011 (including the additional 1,010 that died during 2011) were poached. The 2011 figure is equivalent to a mean of 2. 8 elephants poached daily. Our estimate of 1,010 elephants poached during 2011 is much greater than the number of poached elephants (76) found by field staff and reported to the MIKE programme that year (CITES, 2012). Population model Our study is the first to model simultaneously the numbers of live and dead elephants and to match the modelled trends to survey estimates of elephant and carcass numbers. Application of this approach was facilitated by the consistency between years in survey design, execution and personnel during the Niassa survey programme. The importance of this approach is revealed by the model that mimicked the trend in the number of live elephants only. Although the fit between the modelled and observed elephant numbers (Fig. 4a) was better than the fit produced by the model that mimicked trends in both elephant and carcass numbers (Fig. [SEP] Justify:

Output: The text corroborates the claim by providing evidence that increased mortality of elephants is likely due to illegal hunting, indicating that poaching poses a significant threat to their population. The mention of 'illegal hunting' and specific numbers of poached elephants reinforces the claim about the dangers posed to endangered species like elephants.


Input: Task: contrast the claim using the given text. Claim: All carbohydrates cause weight gain. [SEP] Text: In the Health Center-Study, both weight loss and weight gain of ≥5 kg were associated with an increased risk of all-cause mortality. [25] In the Action to Risk in Diabetes study, researchers observed an asymmetric V-shaped relationship between BMI change and all-cause mortality in patients with type 2 diabetes mellitus. [26] In our study, we reached a similar result when using the 5-year weight change during mid-life as the exposure. However, a decreased risk of cancer mortality was observed among subjects with weight gain ≥5 kg, which was inconsistent with previous studies. Jia et al[27] explored the association of adult weight gain with common health outcomes among 35,989 men and 48,377 women aged 40–59 years. They found that per 5 kg weight gain was associated with a 6% higher risk of cancer mortality in women (HR = 1. 06, 95% CI: 1. 02–1. 10). In the Study, researchers measured the weight status among 3850 adults 3 to 5 times during 14 years, and the results showed that weight gaining ≥0. 45 kg/year over 14 years increased cancer risk by 38% (95% CI: 1. 09–1. 76), compared with maintaining stable weight. [28] A previous review concluded that weight gain or being overweight could increase risk of 13 common cancers, including esophageal adenocarcinoma, cancers of the gastric cardia, colon and rectum, liver, and gallbladder. [29] However, Nicholson et al[30] used cancer registry linked electronic health records from the UK’s to evaluate the association between weight loss and cancer risk, and the results showed that the probability of cancer was initially much higher in patients with unexpected weight loss. Previous research regarding the relationship between body weight status and cancer risk is inconsistent. In the study of Jia et al,[27] obesity-related cancer (such as colorectum cancer and postmenopausal breast cancer) accounted for 53% of all cancer deaths in women and 48% in men, while almost all cancer types included in the Study were obesity-related cancers. [28] However, the distribution of obesity-related cancers in different populations may lead to inconsistent associations between weight change and risk of cancer mortality. [SEP] Justify:

Output: The text contrasts the claim by discussing studies that explore the complex relationship between weight gain and health risks, particularly cancer mortality, rather than attributing weight gain solely to carbohydrate intake. For example, it mentions findings such as 'weight gaining ≥0.45 kg/year over 14 years increased cancer risk by 38%' and that 'the probability of cancer was initially much higher in patients with unexpected weight loss,' indicating that the relationship between weight change and health outcomes is nuanced and not strictly linked to carbohydrate consumption.


Input: Task: pass the claim using the given text. Claim: Cognitive biases influence decision-making and perception. [SEP] Text: Reference Svaldi, Brand and Tuschen-Caffier 24 In another study comparing moderate obesity (BMI 36) using the Wisconsin card sorting task, perseveration errors and the failure to maintain set were both more impaired in BED compared to non-BED obese controls but not TMT, Trail B. Reference Duchesne, Mattos and Appolinario 31 In contrast, in a recent study with high BMI (BMI 45), no differences were observed between BED and non-BED obese controls in Trail B. Reference Galioto, Spitznagel and Strain 32 A study comparing BED (BMI 35) and anorexia nervosa with healthy controls showed that BED was associated with greater set shifting impairments compared to anorexia nervosa as measured during TMT and failure to maintain set in the Wisconsin card sorting task. Reference Aloi, Rania and Caroleo 23 Thus, although the literature is limited, those with BED appear to be impaired in set shifting with greater impairments relative to non-BED obese controls when BMI is low but possibly with similar impairments when BMI is high. Goal-directed, habitual, and perseverative choices Goal-directed and habitual behaviors have been examined in BED using the Two-step task which assesses whether individuals make choices based on the likely affective outcomes (model-based) or based on previously reinforced choices (model-free). Reference Daw, Gershman, Seymour, Dayan and Dolan 37 In this task, subjects choose between 1 of 2 choices, which then leads with fixed probability to 1 of 2 states; selection of the choice at the second stage then leads to a probabilistic reward. Using this task to examine the balance between goal-directed behavior and habit formation, BED compared to non-BED obese subjects had impairment in model-based, goal-directed behavior with a shift toward model-free habitual behaviors. Reference Voon, Derbyshire and Ruck 38 Higher binge eating scores correlated positively with the shift toward habit formation. These findings were similar to other disorders, including methamphetamine dependence and obsessive compulsive disorder, suggesting similarities linked by compulsive behaviors. In healthy controls, greater model-based behaviors were associated with greater volumes of the medial orbitofrontal cortex and caudate. [SEP] Justify:

Output: The text discusses studies on eating disorders and decision-making but does not specifically address cognitive biases influencing decision-making and perception. It focuses on behaviors such as goal-directed versus habitual choices in binge eating disorder (BED), without linking these behaviors explicitly to cognitive biases.


Input: Task: corroborate the claim using the given text. Claim: Poaching poses a major threat to endangered species like elephants. [SEP] Text: These factors combine to fuel the illegal ivory trade (van der Westhuizen, Reference van der Westhuizen2011). Poachers focus on big trophy bulls (Kambako Safaris, pers. comm. ), the loss of which affects the viability of the safari industry and thus the management budget for the Reserve. Management authorities in Niassa must deal with a district-driven rural development agenda on one hand and a conservation agenda on the other. The people living within the Reserve see little value in elephants and thus passively encourage poaching, which brings benefits through income, meat and the removal of potential human–elephant conflict. Reversing this attitude requires the conservation authorities to adopt strategies that give greater benefits to local communities from wildlife, and introduce livelihood strategies that stem vegetation clearance for the expansion of agriculture. thank Anabela Rodrigues, former Director of SGDRN, for providing access to the Reserve aerial survey and law enforcement databases. This analysis is based on the findings of surveys conducted by under contract to SGDRN. Those surveys were funded by USAID, the U. S. Fish and Wildlife Service, and Fauna & Flora International. We also thank the safari operators and SGDRN field staff who provided observations on carcass decomposition. commented on drafts of this 4165. 29. 3. . 46. 1. A report to the 62nd meeting of the of CITES. SC62 Inf. 1. . 368. CrossRef2006. Sociedade para a Gestão e Desenvolvimento da Reserva do Niassa, Maputo, Mozambique. 2009. Sociedade para a Gestão e Desenvolvimento da Reserva do Niassa, Maputo, Mozambique. 2011. Sociedade para a Gestão e Desenvolvimento da Reserva do Niassa, Maputo, Mozambique. 2. 0. . 2002. Sociedade para a Gestão e Desenvolvimento da Reserva do Niassa, Maputo, Mozambique. 2004. Sociedade para a Gestão e Desenvolvimento da Reserva do Niassa, Maputo, Mozambique. 105. of Scientific Unions, Paris, France. 129. Centre for Africa, Addis Ababa, Ethiopia. 48. 108. Http://winfonet. alaska. [SEP] Justify:

Output: The text corroborates the claim by highlighting the impact of poaching on elephants, particularly through the illegal ivory trade and the focus of poachers on trophy bulls. This poaching behavior affects the conservation and management of species within the Reserve, and the text implies that the local community's perception of little value in elephants contributes to this poaching threat. Furthermore, it discusses the need for conservation strategies that provide benefits to local communities in order to reduce poaching, directly linking poaching with the threat to elephant populations.