Input: Task: corroborate the claim using the given text. Claim: Invasive species can disrupt local ecosystems and wildlife. [SEP] Text: the ability to control an invasive species and to protect an ecologically similar native species it is essential to map the exact distributions of both species. This is difficult if the species are so morphologically similar that their identification in the field is almost impossible. In Finland, the invasive beaver Castor canadensis is spreading towards the range of the native Eurasian beaver Castor fiber and at present, these species are partly sympatric. Effective management of these morphologically similar species requires an efficient method for species identification, ideally one that is non-invasive. Non-invasive genetic methods are used in a wide variety of wildlife species, for example in the research of large carnivores. Feces are a good source of DNA for terrestrial animals, but for the semi-aquatic animals like beavers, feces are not the best option. However, environmental DNA (eDNA) has been successfully used to detect species non-invasively in aquatic and terrestrial environments. We developed a non-invasive, eDNA-based method to map the distribution of the beaver species in Finland and to investigate within-species genetic diversity. The eDNA was obtained from the feed remains (wood chips) from beaver forage sites. With the help of Citizen science, wood chip samples were collected from different parts of Finland. We used our eDNA method to identify the ranges of both beaver species. Additionally, the presence of Eurasian beavers in south-east Finland was proven for the first time. Our non-invasive eDNA method is an effective way to accurately identify the ranges of both beaver species and will allow for the control of the invasive beaver and conservation of the native Eurasian beaver in Finland. Invasive species are recognized as one of the worst threats to biodiversity (Ebenhard 1988). When the ranges of ecologically similar invasive and native species approach each other, it is important to control the spread of the invasive species. Therefore, it is essential to map the exact distributions of both species. The method should preferably be non-invasive so that no individuals of the species are disturbed by the procedure. Traditional methods to collect samples for DNA extraction (blood, tissue or hair sample) typically require the capture of the individual. This is not only stressful for the animal but also demanding to implement in field. The use of a non-invasive method is particularly important in the case of an endangered native species. [SEP] Justify:

Output: The text corroborates the claim by discussing the invasive beaver (Castor canadensis) and its spread towards the native Eurasian beaver (Castor fiber) in Finland, emphasizing the importance of controlling the invasive species to protect local biodiversity. The text states that "Invasive species are recognized as one of the worst threats to biodiversity," which directly supports the claim that invasive species can disrupt local ecosystems and wildlife.


Input: Task: contrast the claim using the given text. Claim: A vegan diet is automatically healthier than other diets. [SEP] Text: It is estimated the global value of meat alternative products will reach over £22 billion by 2023(53). Our pattern analyses clearly indicate the vegan food industry is impacting vegan dietary choices. According to Fardet and Boirie(and Boirie54), the health benefits of plant-based diets are closely associated with the fact that such foods require the least amount of processing. In contrast, factor analysis in this study found that the main vegan dietary pattern was a convenience, ultraprocessed diet. Similarly, the third pattern identified represents unhealthy lifestyle behaviours featuring alcohol, takeaways and salt. Cluster analysis reveals clusters 1 and 2 (27 % and 22 % of the sample, respectively) comprised foods such as sauces, condiments, fats, processed meat alternatives and convenience foods. Together these findings are particularly concerning as they raise questions regarding the impact of ultraprocessed foods on the quality of some vegan diets. Despite the growing number of people choosing to follow a vegan diet, there are still no specific official dietary guidelines for vegans in the UK. is a relatively new resource that provides additional supportive information reinforcing key considerations for planning the diet. However, the unexpected findings from this study do not represent the guide. Our cluster analysis showed that although cluster 3 (health conscious) represented most of the participants (51 %) and was made up of an array of healthy foods such as fruit, meat alternatives and vegetables, it did not consist of foods from each of the main food groups. For example, dairy alternative items did not factor at all in this cluster. The main dietary patterns presented in this study depict diets high in processed meat alternatives such as vegan burgers, nuggets, sausage rolls in contrast to natural plant-based proteins such as pulses, soya and tofu, which are recommended on the guide. Potential concerns within vegan dietary patterns Although full nutritional analysis was not conducted in this study, the findings from the factor and cluster analyses suggest some vegan diets are poorly constructed. Within this study, these findings warrant concern that some vegans may be at potential risk of nutritional deficiencies. Respondents were often on more than one supplement, although exact intakes were not recorded. The analysis revealed 68 % were supplementing one or more of the main nutrients of concern(Reference Craig9) representing vitamin B12 (42 %), vitamin D (14 %), n-3 (12 %), iodine (26 %), Fe (19 %), Ca (15 %), Zn and Se (8 %). [SEP] Justify:

Output: The text contrasts the claim by highlighting that while the vegan food industry is growing, the health benefits of plant-based diets are not guaranteed. It mentions that many vegan diets are ultraprocessed, indicating that the main dietary patterns can be unhealthy. The study raises concerns that some vegan diets may be poorly constructed and that vegans are at potential risk of nutritional deficiencies, with 68% of respondents supplementing nutrients of concern. Therefore, it challenges the idea that a vegan diet is automatically healthier.


Input: Task: pass the claim using the given text. Claim: Cognitive biases influence decision-making and perception. [SEP] Text: CrossrefPubMedWeb of Science230. Nexøe J, Gyrd-. Danish GPs’ perception of disease risk and benefit of prevention. Fam Pract. 2002;19(1):3–6. CrossrefPubMedWeb of Science231. Nexøe J, Oltarzewska AM, Sawicka-. Perception of risk information: similarities and differences between Danish and Polish general practitioners. Care. 2002;20(3):183–7. CrossrefPubMedWeb of Science232. Nikolajevic-’Connell DL, Robertson J. Effects of information framing on the intentions of family physicians to prescribe long-term hormone replacement therapy. J Med. 1999;14(10):591–8. CrossrefPubMedWeb of Science233. Perneger TV, Agoritsas T. Doctors and patients’ susceptibility to framing bias: a randomized trial. J Med. 2011;26(12):1411–7. CrossrefPubMedWeb of Science234. . Patients’ self-estimated likelihood of taking a statin as prescribed after different types of prognostic information. Atherosclerosis. 2010;212(2):586–8. CrossrefPubMedWeb of Science235. Sarfati D, Howden-. Does the frame affect the picture? A study into how attitudes to screening for cancer are affected by the way benefits are expressed. J Med Screen. 1998;5(3):137–40. CrossrefPubMedWeb of Science236. A randomized trial of decision-making in asymptomatic carotid stenosis. Neurology. 2012;78(5):315–21. CrossrefPubMedWeb of Science237. Sinsky CA, Foreman-Hoffman V, Cram P. The impact of expressions of treatment efficacy and out-of-pocket expenses on patient and physician interest in osteoporosis treatment: implications for pay-for-performance programs. J Med. 2008;23(2):164–8. CrossrefPubMedWeb of Science238. Straus SE. Individualizing treatment decisions: the likelihood of being helped or harmed. Prof. 2002;25(2):210–24. CrossrefPubMedWeb of Science239. . [SEP] Justify:

Output: The text provided consists mainly of citations and references related to various studies and does not directly discuss cognitive biases or their influence on decision-making or perception. As such, it does not support, contradict, or relate to the claim in a meaningful way.


Input: Task: corroborate the claim using the given text. Claim: Invasive species can disrupt local ecosystems and wildlife. [SEP] Text: beaver Castor fiber is classified as a near threatened species in Finland (Hyvärinen et al. 2019). The original Eurasian beaver was extinct in Finland in late 19th century but has recovered due to releases of 19 individuals from Norway in the 1930s (Lahti and Helminen 1969, 1974, Lahti 1972). Unfortunately, at least seven individuals of beaver C. canadensis from the USA (Parker et al. 2012) were also released into several places in southern and central Finland, because at that time its status as a distinct species was not recognized. beaver disappeared from places where both species were introduced, and its population grew slowly only in the region of Satakunta, south-west Finland (Lahti and Helminen 1980). Its present distribution covers areas in southwest Finland (mainly Satakunta) and western Lapland where beavers probably wandered from Sweden (Fig. 1, Iso-Touru et al. 2020). In addition, some Eurasian beavers likely migrated to south-eastern Finland from where a Eurasian beaver population exists (Danilov et al. 2011a). The introduced, invasive beaver population increased much faster and soon occupied most of eastern and central Finland (Lahti and Helminen 1969). It also occurs sporadically in Lapland, because some were relocated from southern Finland to Lapland (Lahti 1972). Figure 1. The distribution of the native Eurasian beaver and the invasive beaver in Finland based on the monitoring count in 2020. Identification of species was mainly estimated from lodge location but information from DNA analyses of wood chips was also used. For monitoring counts, see Brommer et al. (2017). Green bullets=Eurasian beaver, brown squares=beaver, blue bullets=areas where both species occur. Original figure: Institute Finland, Luke. In recent years, beavers have spread towards the range of the native species in Finland and at present the two species are sympatric in at least three river systems (Kauhala and Karvinen 2018). Because the two beaver species are fairly similar in their habitat use, it is possible that they compete for the best habitat patches with deciduous trees (Kauhala and Turkia 2013, Alakoski et al. 2019). The invasive species has larger litters (Parker et al. [SEP] Justify:

Output: The text corroborates the claim by detailing the introduction of the invasive beaver species (C. canadensis) into Finland, which has led to competition with the native Eurasian beaver (C. fiber) for habitat resources. It indicates that the invasive species has spread rapidly and successfully occupied various regions, suggesting a disruption in the local ecosystem as the two species compete for habitat patches. The mention of the invasive species having larger litters also supports the assertion that invasive species can disrupt local wildlife dynamics.


Input: Task: contrast the claim using the given text. Claim: A vegan diet is automatically healthier than other diets. [SEP] Text: Dairy alternatives were the only identified food group with potential to enhance B12 intakes; however, they only featured in the first identified dietary pattern for factor analysis and in the second cluster which represented only 22 % of the sample. Previous research has established that vegans consume sufficient amounts of dietary Fe, which prevents anaemia(Reference Waldmann, Koschizke and Leitzmann55). Food groups that could provide Fe in the vegan diet include vegetables, protein alternatives to meat/fish and refined (incorporating fortified white flour) grains(Reference Waldmann, Koschizke and Leitzmann55,56) however, these groups did not feature highly in any of identified clusters. The factor analysis also showed none of the identified patterns featured all of these food groups. Adequate consumption of fortified plant milks and soya products such as yoghurt can help vegans to meet dietary requirements for Ca; therefore, dietary adaptations are an important consideration to support bone health(and Garton27). Dairy alternatives were a component in the ‘convenience’ factor analysis dietary pattern but not the other three and did not have a high predictor of importance for in the cluster analysis. This also has potential implications for iodine status in vegans. Cows’ milk is one of the best sources of iodine in the UK diet; however, with plant-based milks more popular than ever before, the UK population are at risk of mild iodine deficiency(Reference Bath, Hill and Infante57,Reference Vanderpump, Lazarus and Smyth58). Vegans fitting the ‘convenience’ dietary pattern did incorporate dairy alternatives, thus potentially meeting iodine requirements. However, the alternative vegan dietary patterns warrant concern as they are all absent of dairy substitutes. This is particularly alarming as the majority of participants in this study were young females, who are thought to be particularly at risk of iodine deficiency in the UK(Reference Bath59). The dietary patterns and clusters ‘convenience’ and ‘unhealthy’ revealed in this study also warrant concern for n-3 status in vegans. It has been reported in the USA that some processed foods, meat substitutes and salad dressings have high quantities of n-6 linolenic acid present, which could further impair n-3 status(Reference Burns-Whitmore, Froyen and Heskey60). [SEP] Justify:

Output: The text contrasts the claim by discussing various potential deficiencies in a vegan diet, including issues with iodine and n-3 fatty acid status, as well as highlighting that dairy alternatives, which can improve nutrient intake, were not prevalent in all dietary patterns identified. This indicates that a vegan diet may not be automatically healthier in terms of nutrient balance and could lead to risks of deficiencies, particularly among specific demographics such as young females.


Input: Task: pass the claim using the given text. Claim: Cognitive biases influence decision-making and perception. [SEP] Text: CrossrefPubMedWeb of Science252. Chao L-. End-of-life medical treatment choices: do survival chances and out-of-pocket costs matter? Making. 2008;28(4):511–23. CrossrefPubMedWeb of Science253. . The effect of offering different numbers of colorectal cancer screening test options in a decision aid: a pilot randomized trial. . 2008;8:4. CrossrefPubMedWeb of Science254. Brody H. Medicine’s ethical responsibility for health care reform: the top five list. N Med. 2010;362(4):283–5. CrossrefPubMedWeb of Science255. Decisions Foundation. Preference-sensitive decisions. Available from: URL:. Anxiety, fear of cancer, and perceived risk of cancer following lung cancer screening. Making. 2008;28(6):917–25. CrossrefPubMedWeb of Science257. . Resisting good news: reactions to breast cancer risk communication. Health Commun. 2006;19(2):115–23. CrossrefPubMedWeb of Science258. The impact of genetic counseling on risk perception and mental health in women with a family history of breast cancer. Cancer. 1999;79(5–6):868–74. CrossrefPubMedWeb of Science259. . Risk perceptions: assessment and relationship to influenza vaccination. Health Psychol. 2007;26(2):146–51. CrossrefPubMedWeb of Science260. . Heuristics in medical and non-medical decision-making. Q J A. 1992;44(2):211–35. CrossrefPubMedWeb of Science261. . Sensitivity to disgust, stigma, and adjustment to life with a colostomy. J Res Pers. 2007;41(4):787–803. CrossrefPubMedWeb of Science262. Gigerenzer G. Gut Feelings: of the Unconscious. New York: Viking; 2007. 10. 11770272989x14547740_table_s1. pdf84. 25 KBds_10. 11770272989x14547740_table_s2. pdf85. 39 KBCite 2014. PubMed: 25145577AuthorsAffiliationsJ. S. Blumenthal-Barby, PhDView all 41. 50 Issue - $186. [SEP] Justify:

Output: The text primarily provides references to various studies and articles related to medical decision-making and perceptions of risk but does not directly address the role of cognitive biases in decision-making or perception. Consequently, it does not support, contradict, or provide information relevant to the claim.


Input: Task: corroborate the claim using the given text. Claim: Invasive species can disrupt local ecosystems and wildlife. [SEP] Text: The number of haplotypes observed are given in (c) and (d) in parentheses after the haplotype name. Mutated positions are shown as vertical lines and node sizes are proportional to frequencies. Median vectors (mv1 and mv1 (haplotypes not present in the current data)) are shown in red. Wood chips were mostly obtained from regions populated by Eurasian beavers. This might partly explain the low amount of C. canadensis haplotypes observed in this study. Furthermore, only about seven individuals of C. canadensis were released, (Lahti 1972) and may have resulted in low genetic diversity due to a founder effect. If more samples were obtained from the Eastern part of Finland (Fig. 1), it is possible that more mtDNA haplotypes for the beavers may have been found. Unlike in Finland, beavers were never relocated to other Scandinavian countries. Live-trapped beaver individuals in Finland were released in the 1940s near the Russian border (Lahti and Helminen 1974). Similar releases of beavers were conducted in Karelia. American beaver population in Karelia has grown and is assumed to have spread north along the Finland-Russian border (Parker et al. 2012). This study confirmed earlier identifications of the beaver species from skull morphometry and some DNA analyses from tissue samples of hunted beavers (Kauhala and Timonen 2016, Iso-Touru et al. 2020) but also provides new information of the distribution of beavers from a larger area. Furthermore, all recent species identifications from Lapland are based on this study, i. e. DNA analysis from wood chips. Beavers have not been hunted in Lapland (so no skulls or tissue samples were obtained from Lapland) in recent years because the distribution of Eurasian beaver there was not known, and hunters need a license to hunt Eurasian beavers in Finland. Therefore, hunters did not want to take the risk that they would illegally kill a Eurasian beaver in Lapland. Our new noninvasive DNA method now enables beaver species identification throughout Finland and thus promotes the control of the invasive beaver and conservation of the native beaver in Finland. It has been suggested that beavers should be removed from areas where the two species are sympatric or live close to each other (Plan for Beavers, in prep. ). [SEP] Justify:

Output: The text corroborates the claim by discussing the impact of invasive beavers on local ecosystems in Finland. It suggests that beavers have been released in non-native areas, which has implications for the conservation of native beaver species. The mention of the need for control measures and removal of beavers where they may disrupt the native species points to their disruptive role in local ecosystems.


Input: Task: contrast the claim using the given text. Claim: A vegan diet is automatically healthier than other diets. [SEP] Text: Thus, nutritional data about the processed vegan products that have recently launched in the UK are urgently required. In contrast to earlier findings, the dietary patterns found in this study suggest some vegan diets are highly processed with lower intakes of natural vegan foods. This is an important consideration especially as evidence reveals the level of processing can affect the nutritional quality of a food(Reference Frontela, Ros and Martínez61,and Mariotti62). In light of the increasing numbers of people choosing to follow a vegan diet and the availability of ultraprocessed vegan food in the market, our findings suggest future studies examining vegan dietary patterns that incorporate nutritional and blood analysis into the study design should be a priority. Strengths and limitations The evolution of a vegan diet when adapted to replace all animal foods with plant-based sources is important. This study is among the first to research the vegan diet specifically, identifying recent dietary patterns in a UK vegan cohort. It is unique for its distribution technique of social media, effectively recruiting a convenience sample to complete the FFQ. Vegan adaptation of the validated allowed participants to select from over 150 food items with a wide range of plant-based meat and dairy alternatives represented. Participants had the option to select ‘other’ ensuring a wide range of vegan food and drink items were captured. However, some limitations must be considered. The current analyses were based on a small convenience sample of 129 vegans, recruited through social media, which may affect the validity of the results. The recruitment phase was limited as the COVID-19 pandemic emerged in the UK. The research team was redeployed from their usual roles, and a decision was made to stop recruiting to the study to ensure sufficient time to analyse the data. To address demographical limitations, future studies should aim to increase the diversity of participants across gender and ethnicity, amend the inclusion criteria to vegans who have followed the diet for longer than 12 months and include more sociodemographical questions. Although the steps were taken to validate the adapted FFQ, further measures may help to enhance validity. Adapted FFQ are not compatible with into Cancer and for Analysis (FETA) software; therefore, it may be more appropriate in future studies to ask a subsample of participants to complete a 3-d, 24 h weighed multiple pass recall (24 h MPR) outlining typical portion sizes to validate the FFQ responses(Reference Adamson, Collerton and Davies63). [SEP] Justify:

Output: The text contrasts the claim by indicating that some vegan diets may be highly processed and include lower intakes of natural vegan foods. It emphasizes the need for nutritional analysis of such diets, suggesting that the level of processing can affect the nutritional quality of food. Therefore, it challenges the assumption that a vegan diet is automatically healthier.


Input: Task: pass the claim using the given text. Claim: Cognitive biases influence decision-making and perception. [SEP] Text: The model corresponds to a SIR (susceptible-infected-recovered/immune) compartmental model capturing the disease transmission process [30] augmented with a belief model (Fig 1). It enables individuals to be characterized by both their epidemiological status and their opinion. Specifically, individuals can belong to one of 4 epidemiological compartments: susceptible, infected, immune through vaccination and immune naturally. In each compartment, individuals can be characterized either as “pro-vaccines” (positive opinion) or “sceptical” (negative opinion). Across time, individuals can change compartments: for instance, susceptible individuals may become infected, or they may choose to vaccinate. The system of compartments and flows between them is defined by a system of ordinary differential equations (see section 2. iii) to examine numerical simulations at different values of the parameters. Download: PPTPowerPoint slidePNGlarger imageTIFForiginal imageFig 1. Structure of the behaviour-incidence model. The model is an augmentation of a classic SIR compartmental model [30]. Individuals are characterized by both their epidemiological status (S: susceptible; I: infected; Rv: recovered through vaccination; Rg: recovered naturally) and for each compartment, their opinion of vaccination (positive: subscript p; non-shaded colours; negative: subscript n; shaded colours). CV and CI are compartments that indicate the total recalled number of individuals having suffered negative side effects from vaccination and infection, respectively. β indicates the rate of infection transmission; Ω indicates the rate at which individuals change their opinion (from positive to negative Ω or from negative to positive Ω′); δ indicates the number of individuals suffering side effects from either vaccination δV and infection δI; θ indicates the rate at which individuals vaccinate. Each individual dies at the same rate d. rate at which individuals become vaccinated is a function of both the epidemiological costs associated with infection and vaccination and the distribution of opinions of vaccination in the population. First, costs are defined by the epidemiology with the number of infected individuals and vaccination coverage determining the number of people suffering negative side effects from infection and vaccination, respectively. Individuals are assumed to vaccinate more quickly when the infection cost is high and more slowly when the vaccination cost is high. [SEP] Justify:

Output: The text does not directly address the claim that cognitive biases influence decision-making and perception. Instead, it discusses a SIR compartmental model related to disease transmission and vaccination opinions without linking these concepts to cognitive biases or decision-making processes.


Input: Task: corroborate the claim using the given text. Claim: Invasive species can disrupt local ecosystems and wildlife. [SEP] Text: Using this eDNA method the ranges of beaver species can be accurately identified in the critical areas where beaver species are sympatric or live close to each other. This helps selective hunting of the invasive species. ConclusionsWe present here a non-invasive DNA based method to identify beaver species from environmental samples. The method uses wood chips that beavers leave at the foraging site. The wood chip samples are easy to collect and simple to store before processing. The developed extraction method can be used to monitor the detailed distributions of the two beaver species in Finland. Precise monitoring will help to control the spread of the invasive beaver and to enable the spread of the native beaver in country. Our method is easily applied to monitor species that leave feed remnants that can be collected in the field. Feed remnants are an option to use eDNA and monitor (semi-aquatic) animals that do not leave feces which are easily found. The method can be used not only for species identification but potentially also to identify individuals by using multiple genetic markers. Acknowledgements – The authors want to thank numerous anonymous volunteers for the woodchip sample collection. Niinimäki is acknowledged for providing the C. canadensis reference samples from Ähtäri Zoo. Funding – The study was partly funded by the Suomen riistanhoitosäätiö. Conflict of interest – The authors declare no conflict of interest. Author contributionsKK and TIT designed the study, JT and AV developed the extraction method and genotyped the samples. TIT and KK analyzed the data. TIT and KK wrote the manuscript. All authors read and approved the final manuscript. 1. Alakoski, R. et al. 2019. Similarities in habitat use between the native Eurasian beaver and the invasive beaver in Finland. – Biol. Invas. 21: 1601–1613. 2. Bandelt, H. et al. 1999. Median-joining networks for inferring intraspecific phylogenies. – Mol. Biol. Evol. 16: 37–48. 3. Brommer, J. E. et al. 2017. Population dynamics of the native Eurasian beaver and the invasive beaver in Finland inferred from citizen-science census data. – Ecosphere 8: e01947. 4. Danilov, P. et al. 2011a. [SEP] Justify:

Output: The text corroborates the claim by discussing the management of invasive beavers and how the monitoring method developed allows for the control of their spread. The emphasis on selectively hunting invasive species to enable the spread of native species underlines the disruption that invasive species can pose to local ecosystems, aligning well with the claim.


Input: Task: contrast the claim using the given text. Claim: A vegan diet is automatically healthier than other diets. [SEP] Text: This would allow future nutritional analysis similar to the work carried out in other studies(Reference Clarys, Deliens and Deliens23,Reference Janssen, Davies and Richardson39). It would have been interesting to perform blood analysis on the participants to compare the nutritional status within each of the identified dietary patterns. Future research utilising interviews could also explore why vegans eat what they do providing a more in depth insight into current vegan dietary patterns. In conclusion, this study is the first to highlight the necessity of further investigations into vegan dietary patterns, particularly as there may be newly emerging dietary patterns that conflict with traditional vegan dietary patterns. If vegan dietary patterns are changing, it is prudent to consider the implications these new dietary choices may be having on health. Factor analysis identified four patterns within the vegan diet: (1) convenience; (2) health conscious; (3) unhealthy and (4) traditional in a cohort of 129 vegans. Whilst two healthy patterns were defined, the convenience pattern was the most identifiable pattern with a prominence of vegan convenience meals and snacks, vegan sweets and desserts, sauces, condiments and fats. Cluster analysis further strengthens these findings by confirming, that like the dietary patterns, the most predominant clusters consisted of an array of processed vegan food items. The association between these processed products is noteworthy considering the growth of veganism and the food industry’s response to this by providing a rapid rise in the production of vegan products. Future research has potential to further verify our findings by collecting a proportion of weighed 24 h MPR from participants to determine exact portion sizes before undertaking nutritional analysis, following factor and cluster analyses. This research is a starting point but does raise some interesting questions regarding vegan dietary patterns, while the vegan food industry continues to grow. The findings from this small study have potential to shape and influence future vegan research. This novel study highlights the need for further vegan dietary pattern analysis studies that include nutritional and metabolic evaluation, particularly well-powered multicentre studies to ratify these results. Acknowledgements Acknowledgements: None. Financial support: This research did not receive any specific grant from funding agencies in the public, commercial or not-for-profit sectors. Conflict of interest: There are no conflicts of interest. Authorship: C. T. G. was responsible for researching, writing and preparing of the manuscript, proof reading and corrections. P. H. assisted with the factor and cluster analyses. K. E. L. [SEP] Justify:

Output: The text contrasts the claim by indicating that while two patterns identified within vegan diets are categorized as healthy, there is also a predominant pattern comprised of processed vegan foods, described as the 'convenience' pattern. This suggests that not all vegan dietary patterns are healthy and raises questions about the health implications of evolving vegan food choices, implying that a vegan diet is not automatically healthier than other diets.


Input: Task: pass the claim using the given text. Claim: Cognitive biases influence decision-making and perception. [SEP] Text: The rate of infection transmission: β is expressed in terms of the basic reproductive ratio of the pathogen R0 [31]. R0 corresponds to the average number of secondary infections produced by an infected individual in an otherwise susceptible population and can be understood as the fitness of the pathogen: for a pathogen to invade the population, R0 must be >1. In our model R0 has been calculated as: where and are determined numerically using the system of ordinary differential equations (see section 2. iii) assuming no infection. Download: PPTPowerPoint slidePNGlarger imageTIFForiginal imageTable 1. Parameters used and their default values. S* is the number of susceptible individuals, i. e. the number of individuals that are not vaccinated before the emergence of the infection. In our model, people can have two different opinions regarding vaccination which implies two different probabilities to accept the vaccine. Thus the number of susceptible individuals S* depends on the number of individuals who either have a positive or a negative opinion before the emergence of the infectious disease, i. e. where and represent the population equilibrium of the number of susceptible individuals in the absence of disease. The information relating to the costs of infection and vaccination: This information, available to everyone, is assumed to be summarized by a function of the number of the past and present individuals who have suffered negative side effects from infection and vaccination. This information is used by all individuals in order to measure the relating costs of infection and vaccination, respectively denoted CI and CV. We supposed that this information is generated and memorized by all individuals at a rate δI and δV. We also assumed that the information is forgotten at a rate f. At any given point in time, the number of infected individuals is determined by the history of vaccine uptake in the population. Thus, the costs of infection and vaccination depend on both the history of vaccine uptake and the number of infected individuals. The rate of vaccination: Only susceptible individuals can take up vaccination and the decision to vaccinate depends on both an individual opinion and the costs of infection and vaccination. Individuals with a positive opinion vaccinate at the rate θp; individuals with a negative opinion vaccinate at the rate θn. υp and υn represent the maximum rate at which individuals can be vaccinated. [SEP] Justify:

Output: The text is irrelevant to the claim as it discusses mathematical modeling of infection transmission, vaccination rates, and public opinions towards vaccination. It does not mention cognitive biases nor their influence on decision-making or perception.


Input: Task: corroborate the claim using the given text. Claim: Greenhouse gas emissions trap heat in Earth’s atmosphere. [SEP] Text: Главная Научные конференции “Prospects and of Science in Contemporary World” Опубликовано в конференции: “Prospects and of Science in Contemporary World” Автор(ы): Оразалина Динара Кайыргалиевна Рубрика конференции: Секция 14. Технические науки DOI статьи: 10. 32743/SpainConf. 2022. 7. 21. 344063 Библиографическое описание Оразалина Д. К. // Proceedings of the «Prospects and of Science in Contemporary World». S. L. , Madrid, Spain. 2022. DOI:10. 32743/SpainConf. 2022. 7. 21. 344063 Авторы Оразалина Динара Кайыргалиевна candidate, Almaty technological university, date, the trend to contribute to climate change is gaining momentum and is being considered at the state level. The impact of humanity on emissions into the atmosphere and environmental pollution is enormous. This dynamically reflects climate change, as a result - an increase in air temperature. In developing countries, they pay special attention to individual sustainable development goals. Keeping the industrial sector in phase is "environmentally friendly" without increasing greenhouse gas emissions into the earth's atmosphere, one of the goals of sustainable development. Responding to the challenges of the current trend of containment and development of technological solutions is the fundamental goal of combating climate change. [SEP] Justify:

Output: The text corroborates the claim by discussing the impact of greenhouse gas emissions on climate change and air temperature. It mentions that humanity's emissions into the atmosphere have a significant impact and contribute to an increase in air temperature, which aligns with the understanding that greenhouse gas emissions trap heat in Earth’s atmosphere.


Input: Task: contrast the claim using the given text. Claim: A vegan diet is automatically healthier than other diets. [SEP] Text: Contrasts of diet patterns were most often rated 6 or 7, with a smallest contrast of 1 (comparing patterns based on total fat alone) to a largest of 10 (comparing 3 healthier home-cooked meals to 3 fast food meals). Compared with unweighted comparisons, the intensity-weighted price differences of healthier versus less healthy food-based diet patterns were similar: $1. 46/day ($1. 00 to $1. 92) and $1. 53/2000 kcal ($1. 14 to $1. 93; supporting figure 3). Intensity-weighted price differences were also similar to unweighted results for nutrient-based diet patterns: $0. 11/day (−$0. 64 to $0. 85) and $1. 66/2000 kcal ($0. 55 to $2. 78; supporting figure 4). Potential sources of heterogeneity Statistical heterogeneity as quantified by the I2 statistic was high in most analyses. Metaregression did not identify significant effect modification based on study location (USA/Canada vs other), intensity of the contrast in healthfulness or study type (market survey vs dietary survey) (data not shown). Metaregression by study type (market survey vs dietary survey) was not possible for the food group analyses due to collinearity. Publication bias Publication bias was assessed using the Egger test and funnel plots (supporting figure 5). 20 There was no significant bias identified by the Egger test. Visual inspection of funnel plots suggested asymmetrical distributions for dairy food, food-based diet patterns and nutrient-based diet pattern comparisons, consistent with a larger number of smaller studies reporting greater price differences than the overall pooled estimate. findings from this systematic review and meta-analysis provide the most robust evidence until today on price differences of healthier versus less healthy foods and diet patterns. The results by food group provide insight into the relationship between healthfulness and price among similar foods. The results by diet pattern inform price differences for larger extremes of healthfulness, comparing very different foods, for example, diets rich in fruits and vegetables versus diets rich in processed foods. Although statistical heterogeneity was high, this was at least partly related to relatively small statistical uncertainty of each within-study price difference. The magnitude of clinically relevant heterogeneity was much lower, with comparatively similar price differences between studies. [SEP] Justify:

Output: The text contrasts the claim by discussing the complexities of diet comparisons rather than asserting that one specific diet (such as a vegan diet) is automatically healthier. It mentions various dietary patterns and states that there is evidence related to price differences between healthier and less healthy foods, but does not affirm the inherent superiority of a vegan diet. It suggests that healthiness in diets is nuanced and influenced by multiple factors, which undermines the notion of automatic health benefits associated with any specific diet, including veganism.


Input: Task: pass the claim using the given text. Claim: Cognitive biases influence decision-making and perception. [SEP] Text: To evaluate the role of each component of the full model in shaping the dynamics of infection and vaccination coverage, we analysed and compared the results of the nested models. We run all models for values of R0 ranging from 0 to 10 in steps of 0. 5. All other parameter values are detailed in Table 1. ResultsOur results are threefold: (i) for all parameter values investigated, the infection is never eradicated under voluntary vaccination, i. e. vaccination coverage never reaches herd immunity, that is, the threshold of vaccination coverage needed for stopping the spread of the infection; (ii) the dynamics of infection and vaccination coverage depend on the presence/absence of a polymorphism for the opinion of individuals, which is a function of the transmissibility potential of the pathogen (R0) (Fig 2). If the infection is not contagious (R0 < 1), all individuals become sceptical and vaccination coverage remains low; if infection is highly contagious (R0 >> 1), all individuals become pro-vaccines but herd immunity is never reached because the infection spreads too quickly. Yet, vaccination coverage remains high. For intermediate values of R0, both sceptical and pro-vaccine individuals coexist and oscillations in vaccination coverage are observed (Fig 3); (iii) the rule “imitate the majority” is not necessary for oscillations to appear. Rather, the transmission of opinions through conformism increases the delay between changes in epidemiological parameters and the behavioural responses to those changes (Fig 4). Download: PPTPowerPoint slidePNGlarger imageTIFForiginal imageFig 2. Infection and opinion dynamics as a function of the reproductive rate of the infection (model 5). For each value of R0 (number of secondary infections which can be understood as the fitness of the pathogen; it must be >1 for the pathogen to invade the population), the time-series of the dynamics of the infection (top panel; the thin line corresponds to the number of infected individuals and the thick line corresponds to the number of vaccinated individuals) and opinion (bottom panel; the dashed grey line indicates the number of individuals who have a positive opinion and the dashed black line indicates individuals who have a negative opinion) are depicted for a rate of negative side effects from vaccination δv = 0. 7. Alternative changes of opinions of vaccination and oscillations in vaccination coverage emerge for intermediate values of R0. [SEP] Justify:

Output: The text does not directly address the influence of cognitive biases on decision-making and perception. Instead, it discusses models related to infection dynamics and vaccination coverage, and the transmission of opinions without linking these models to cognitive biases. Therefore, it is irrelevant to the claim.


Input: Task: corroborate the claim using the given text. Claim: Greenhouse gas emissions trap heat in Earth’s atmosphere. [SEP] Text: new wave of being in the trend of environmental issues is making many researchers reproduce the future portrait of the situation in Kazakhstani ecology, at glance. The most common issue is in the production industries. Where the waste is monitored by the state. According to the official information resource of the of the Republic of Kazakhstan in 2019: "Zone of Almaty operates for the development of the industrial sector. The total area of the territory is 490 hectares. According to the statistics department of Almaty, 1. 5 thousand companies are operating industrial enterprises. Industrial enterprises produce reinforced concrete products, asphalt, concrete, aluminum profiles, paint and varnish products, etc. In 2019, building materials enterprises produced products worth 54. 3 billion tenges, or 107. 7%. [8]. The main sources of air pollution in the city of Almaty are heating enterprises, which are provided by 3 heat sources through the line of "Almaty electric station” () (CHPP-1, CHPP-2, Complex) and 83 boilers of "and utility energy" LLP, these are 76% of the townspeople, the remaining 24% receive heat from autonomous heat sources and private houses are heated by gas. High air pollution index: 7 (normal up to 5). Exceeding the maximum permissible concentration of NO2 by 2 times, PM2. 5 by 3 times. Growth in the volume of waste, out of 430 thousand tons of MSW, only 17% is recycled. The key issue for the current development challenges of the city of Almaty is the environment, in particular, the clean air of the city for the residents of the metropolis. Thus, it is planned to switch the thermal power plant from the consumption of thousands of fossil solid fuels to gas in 2024. This solution will reduce harmful emissions. For example, CHP-2 accounts for a quarter of the city's carbon dioxide emissions, which is about 35,000 tons per year. Its gas conversion will reduce them by 15 times to 2,3 thousand tons. Toxic substances such as sulfur dioxide and soot will disappear completely [9]. The scientific paper named "Waste gasification processes for SNG production" which was researched by Hermann Hofbauer, and - provides an overview of the state of waste gasification and presents promising technologies for further development. [SEP] Justify:

Output: The text supports the claim by detailing the impact of carbon dioxide emissions from thermal power plants, stating that CHP-2 accounts for a quarter of the city's carbon dioxide emissions, which is about 35,000 tons per year. It also mentions that reducing these emissions by switching fuels will significantly decrease harmful gases, corroborating the understanding that greenhouse gases contribute to heat retention in the atmosphere.


Input: Task: contrast the claim using the given text. Claim: A vegan diet is automatically healthier than other diets. [SEP] Text: In addition, with a few exceptions, findings were similar across different units of price (per serving or day or calorie), intensity of contrast, study location and type of survey, thereby increasing the confidence in the validity and consistency of the findings. Price differences of foods Among six food groups, relatively large price differences were observed for meats/protein, as well as smaller but statistically significant differences for snacks/sweets, grains, fats/oils and dairy. According to the USDA, the farm share of proceeds of a $1 expenditure on domestically produced food in the USA is 14. 1 cents (in 2010),21 suggesting that final retail prices are determined largely by other industries and procedures in the food supply chain. Additional cost of processing and manufacturing could explain some of the identified variation in price differences; for example, lean beef and skinless chicken require more processing, perhaps accounting for their higher price. Our findings highlight the need for more research on the underlying drivers of price differences of specific items within broad food categories. Our findings also demonstrate that, for certain metrics of healthfulness, the selected unit of comparison alters the results. In particular, metrics based largely on fat content demonstrated greater price differences per calorie than per serving. The most striking example was for dairy foods: healthier options were $0. 004 less expensive per serving but $0. 21 more expensive per 200 kcal. Whole milk contains nearly twice the calories as fat-free milk,17 so nearly double the amount of fat-free milk must be purchased to achieve equivalent calories. These findings highlight the dangers of circular reasoning (eg, selecting a metric based on fat content and then evaluating price differences per calorie) and the importance of identifying the most relevant unit of comparison for any individual or public health decision about price differences of foods. 11 Price differences of diet patterns On average, healthier food-based diet patterns were more expensive than less healthy patterns, whether based on an actual day's intake or per 2000 kcal. The price difference—about $1. 50/day—represents the price difference per person for consuming a much healthier versus much less healthy overall diet, for example, comparing Mediterranean-type diets rich in fruits, vegetables, fish and nuts versus diets rich in processed foods, meats and refined grains. Thus, this price difference is for a relatively extreme contrast between the healthiest and least healthy diet pattern. Better adherence to such food-based diet patterns consistently relates to improved health and lower risk of chronic diseases. [SEP] Justify:

Output: The text contrasts the claim by discussing the price differences of healthier versus less healthy food-based diet patterns. It states that healthier diets tend to be more expensive and implies that healthier options vary significantly in dietary content, suggesting that a vegan diet, which might be perceived as healthy, is not inherently healthier than other diet patterns such as the Mediterranean diet. Furthermore, it highlights that better adherence to varied food-based diet patterns relates to improved health and lower risk of chronic diseases, not solely a vegan diet.


Input: Task: pass the claim using the given text. Claim: Cognitive biases influence decision-making and perception. [SEP] Text: In: Manfredi P, D’Onofrio A, editors. Modeling the interplay between human behavior and the spread of infectious diseases. Springer Science+New York; 2013. 19. 3. Manfredi P, D’Onofrio A, editors. Modeling the interplay between human behavior and the spread of infectious diseases. Springer; 2013. 4. . Group interest versus self-interest in smallpox vaccination policy. . 2003;100: 10564–10567. pmid:12920181 View 5. . Vaccination and the theory of games. . 2004;101: 13391–4. pmid:15329411 View 6. Chen FH. A susceptible-infected epidemic model with voluntary vaccinations. J Math Biol. 2006;53: 253–272. pmid:16758209 View 7. -Jimenez P. Patterns of vaccination acceptance. Med. 1999. 1716. pmid:10574240 View 8. . Simple heuristics and rules of thumb: Where psychologists and behavioural biologists might meet. Behavioural Processes. 2005. 124. pmid:15845293 View 9. Todd PM [Ed], [Ed]. Ecological rationality: Intelligence in the world. Ecological rationality: Intelligence in the world. Online; 2012. View 10. Gigerenzer G, Selten R, editors. Bounded rationality: the adaptive toolbox. The MIT Press; 2001. 11. . Social and psychological factors underlying adult vaccination behavior: lessons from seasonal influenza vaccination in the US and the UK. Vaccines. 2013;12: 893–901. pmid:23944683 View 12. . Meta-analysis of the relationship between risk perception and health behavior: the example of vaccination. Health Psychol. 2007;26: 136–145. pmid:17385964 View 13. Perisic A, Bauch C. Social contact networks and the free-rider problem in voluntary vaccination policy. PLoS Comput Biol. 2009;5: e1000280. pmid:19197342 View 14. Perisic A, Bauch CT. Social contact networks and disease eradicability under voluntary vaccination. PLoS Comput Biol. 2009;5. pmid:19197342 View 15. . Imitation dynamics of vaccination behaviour on social networks. Sci. [SEP] Justify:

Output: The text provides a list of references and titles related to vaccination and human behavior but does not discuss cognitive biases or their influence on decision-making. Therefore, it is irrelevant to the claim.


Input: Task: corroborate the claim using the given text. Claim: Climate change is causing more extreme weather events worldwide. [SEP] Text: Stat. 93:(2):575–89 [Crossref] [2012. . The economic growth impact of natural disasters in developing countries: evidence from hurricane strikes in the and Caribbean regions. . J. Dev. Econ. 97:(1):130–41 [Crossref] [2020. . Coastal wetlands reduce property damage during tropical cyclones. . PNAS 117:(11):5719–25 [Crossref] [2022. . The role of insurance in integrated disaster risk management with a focus on how insurance can support climate adaptation and disaster resilience. . 2022 2022. . Wetlands, flooding, and the Act. . Am. Econ. Rev. 112:(4):1334–63 [Crossref] [2018. . The economic impacts of climate change. . Rev. Environ. Econ. Policy 12:(1):4–25 [Crossref] [1999. . Economic analysis of natural disasters. . In Climate, Change and Risk, ed. 27. London:: Routledge. , 1st ed. . [2015. . for Reduction 2015–2030. Geneva:: UNDRR [2022. . Report 2022: Too Little, Too Slow. World at Risk. Nairobi:: UNEP [2019. . Meta-analyses of factors motivating climate change adaptation behaviour. . Nat. Clim. Change 9::158–63 [Crossref] [2024. . Unmitigated disasters? Risk sharing and macroeconomic recovery in a large international panel. . J. Int. Econ. [2015. . Climate Shock: Consequences of a Hotter Planet. Princeton, NJ:: Princeton Univ. Press [2009. . On modeling and interpreting the economics of catastrophic climate change. . Rev. Econ. Stat. 91:(1):1–19 [Crossref] [2023. . Report 2023. Geneva:: World Econ. Forum. [2008. . Coping with disaster: the impact of hurricanes on international financial flows, 1970–2002. . BE J. Econ. Anal. Policy 8:(1). [2020. . Using publicly available satellite imagery and deep learning to understand economic well-being in Africa. . Nat. Commun. 11::2583 [Crossref] [2023. . Extreme heat in North America, Europe and China in July 2023 made much more likely by climate change. Rep. [SEP] Justify:

Output: The text corroborates the claim by presenting evidence that extreme heat experienced in North America, Europe, and China in July 2023 has been made much more likely by climate change. This directly supports the notion that climate change is influencing the frequency and severity of extreme weather events.


Input: Task: contrast the claim using the given text. Claim: A vegan diet is automatically healthier than other diets. [SEP] Text: 2223 In contrast to the findings for food-based diet patterns, healthier versus less healthy nutrient-based diet patterns were not significantly different in price when based on a day's actual intake, but only cost more when standardised to 2000 kcal. These results mirror those observed when comparing individual food groups, such as dairy, based on single-nutrient metrics of healthfulness. These findings emphasise the crucial role of the unit of comparison when comparing prices by nutrient-based metrics. Healthier diets defined based on fibre or fat content will, by definition, have fewer calories, so they will naturally cost more per calorie. Yet, such diets will not necessarily cost more per serving or per meal. In the setting of a global obesity pandemic, assessing price differences per calorie may make little sense when a healthier diet also leads to reductions in total calorie consumption. Growing evidence also indicates that single or selected nutrients are less useful for distinguishing effects on major chronic diseases than types of foods and food-based diet patterns. 13 most comparisons, statistical heterogeneity as measured by I2 was high. Yet, adjustment for intensity of differences in healthfulness had little effect on pooled price differences, and meta-regression revealed no significant effect modification by intensity, study location or study type. The high I2 values may be partly explained by the relatively small statistical uncertainty for each within-study price difference. In many of the identified studies, the combination of a continuous outcome (price) and a relatively large number of samples (foods or individuals) resulted in low uncertainty of each study-specific price difference. A lower within-study uncertainty produces higher I2 values, even when absolute magnitudes of price heterogeneity among studies may be modest from a public health or practical perspective. For example, the price differences among snacks/sweets studies fell within a relatively limited range (−$0. 04 to $0. 30/serving), with a reasonable summary estimate of $0. 12/serving, but statistical heterogeneity was high (I2=85. 9%) partly due to narrow within-study CIs. Thus, the calculated heterogeneity in each summary estimate should be interpreted in light of the actual range of observed price differences across studies. Since clinically relevant heterogeneity was lower than statistical heterogeneity, the pooled results provide an insight into average price differences between healthier and less healthy foods and diet patterns. Although similar classes of foods and diet patterns were evaluated separately, the foods or diet patterns within each category were not exactly the same. [SEP] Justify:

Output: The text contrasts the claim by discussing the complexities of evaluating diet patterns based on healthfulness and price. It argues that healthier diets, which may include vegan options, do not consistently outperform less healthy diets when factors like cost per calorie and calorie consumption are considered. The text emphasizes the importance of food types and food-based diet patterns over single nutrients in assessing diet healthfulness, suggesting that the assumption of a vegan diet being automatically healthier does not hold under scrutiny.


Input: Task: pass the claim using the given text. Claim: Cognitive biases influence decision-making and perception. [SEP] Text: 2011;278: 42–49. pmid:20667876 View 16. . The impact of personal experiences with infection and vaccination on behaviour-incidence dynamics of seasonal influenza. Epidemics. 2012;4: 139–151. pmid:22939311 View 17. Bauch C. Imitation dynamics predict vaccinating behaviour. B. 2005;272: 1669–1675. View 18. . The influence of popular media on perceptions of personal and population risk in possible disease outbreaks. Soc. 2013;15: 103–114. View 19. Caprara A. Cultural interpretations of contagion. Int Heal. 1998;3: 996–1001. View 20. Scherer CW, Cho H. A of Risk Perception. Risk Anal. Blackwell Publishing, Inc. ; 2003;23: 261–267. pmid:12731811 21. Durbach N. Bodily Matters: The Anti-in England, 1853–1907. Press; 2004. 22. Oraby T, Bauch CT. Bounded rationality alters the dynamics of paediatric immunization acceptance. Sci Rep. 2015;5: 10724. pmid:26035413 View 23. Bruner JS, Postman L. On the perception of incongruity: a paradigm. J Pers. Ltd; 1949;18: 206–223. pmid:15409076 View 24. Nickerson RS. Confirmation bias: A ubiquitous phenomenon in many guises. Psychol. 1998. 220. View 25. -Buzaglo J. Cognitive processes and the decisions of some parents to forego pertussis vaccination for their children. J Clin Epidemiol. 1996;49: 697–703. pmid:8656233 View 26. . Parental beliefs and decision making about child and adolescent immunization: from polio to sexually transmitted infections. J Pediatr. 2005;26: 441–452. pmid:16344662 View 27. . The influence of social norms on the dynamics of vaccinating behaviour for paediatric infectious diseases. Sci. 2014;281: 20133172. pmid:24523276 View 28. Coelho FC, Codeço CT. Dynamic modeling of vaccinating behavior as a function of individual beliefs. PLoS Comput Biol. 2009;5. [SEP] Justify:

Output: The text provided discusses various academic references related to vaccination behavior and decision-making without directly addressing the influence of cognitive biases on these processes. While it mentions topics related to behavior and decision-making, it does not specifically link cognitive biases to these concepts, making it irrelevant to the claim.


Input: Task: pass the claim using the given text. Claim: Climate change is causing more extreme weather events worldwide. [SEP] Text: J. Environ. Econ. Manag. 65:(3):361–76 [Crossref] [2017. . Mangroves as a protection from storm surges in a changing climate. . Ambio 46:(4):478–91 [Crossref] [2021. . Resilience of the to Natural Disasters. London:: Cent. Econ. Policy Res. [2023. . Trouble awaits Florida's housing market as the state just lost another home insurer. . Fortune, July 22. [2019. . The economic impacts of natural disasters: a review of models and empirical studies. . Rev. Environ. Econ. Policy 13:(2):167–88 [Crossref] [2018. . Natural disasters, social protection, and risk perceptions. . World Dev. 104::310–25 [Crossref] [2015. . Psychological responses to the proximity of climate change. . Nat. Clim. Change 5:(12):1031–37 [Crossref] [2016. . Opportunities for advances in climate change economics. . Science 352:(6283):292–93 [Crossref] [2021. . Using satellite imagery to understand and promote sustainable development. . Science 371:(6535):eabe8628 [Crossref] [2016. . Social and economic impacts of climate. . Science 353:(6304):aad9837 [Crossref] [2022. . Valuing the global mortality consequences of climate change accounting for adaptation costs and benefits. . Q. J. Econ. 137:(4):2037–105 [Crossref] [2018. . Identifying the economic impacts of climate change on agriculture. . Annu. Rev. Resour. Econ. 10::361–80 [Crossref] [2021. . A conceptual framework for cross-border impacts of climate change. . Glob. Environ. Change 69::102307 [Crossref] [2017. . The legacy of natural disasters: the intergenerational impact of 100 years of disasters in Latin America. . J. Dev. Econ. 127::209–33 [Crossref] [2018. . Adaptation to climate change: a review through a development economics lens. . World Dev. 104::183–96 [Crossref] [2019. . Human migration in the era of climate change. . Rev. Environ. Econ. [SEP] Justify:

Output: The text does not directly address the claim regarding climate change causing more extreme weather events. Instead, it lists various studies related to climate change, resilience, economic impacts of natural disasters, and social responses, none of which explicitly corroborate or contrast the claim about the connection between climate change and extreme weather.


Input: Task: contrast the claim using the given text. Claim: A vegan diet is automatically healthier than other diets. [SEP] Text: The rating system for intensity of contrast was subjective; yet, the ratings were assigned independently and in duplicate with good concordance and provide important sensitivity analyses on the robustness of the results. Our findings on price differences per day and per 2000 kcal reflect an adult diet; the summary estimates should be adjusted for other caloric intakes, for example, in young children. Only English-language studies from PubMed were included, so some studies may have been missed. Given the absence of accepted criteria for judging the quality of observational studies, quality of studies was not formally assessed. Most of the comparisons were from high-income countries, highlighting the need for similar studies in low-income and middle-income nations. sum, our findings provide the most complete evidence until today on price differences of healthier foods and diet patterns, while also highlighting the importance of carefully considering the metric of healthfulness, intensity of contrast and unit of comparison. Our results indicate that lowering the price of healthier diet patterns—on average ∼$1. 50/day more expensive—should be a goal of public health and policy efforts, and some studies suggest that this intervention can indeed reduce consumption of unhealthy foods. 24–26 It remains an open question as to why healthier diets cost more. Some have argued that US agricultural subsidies for commodities (eg, corn and soy) lower the price of less healthy, more processed foods compared with unprocessed foods. 27 However, careful economic analyses demonstrate that the main impact of such subsidies is a direct income transfer to farmers, with little influence on retail prices; and that tariffs and other protectionist policies are actually raising the prices of many commodities such as sugar. 28–30 Conversely, many decades of policies focused on producing inexpensive, high volume commodities have led to a complex network of farming, storage, transportation, processing, manufacturing and marketing capabilities that favour sales of highly processed food products for maximal industry profit. 31 Based on these experiences, efforts to create an infrastructure and commercial framework that facilitates production, transportation and marketing of healthier foods could increase the availability and reduce the prices of more healthful products. 31 Taxation of less healthy foods and subsidies for healthier foods would also be an evidence-based intervention to balance price differences. 31 Other potential barriers to a healthier diet exist, such as availability and cultural acceptability. However, our findings suggest that for socioeconomically disadvantaged populations, the relatively higher cost of healthy foods may be an impediment to eating better. [SEP] Justify:

Output: The text contrasts the claim by suggesting that price differences and accessibility impact the healthfulness of diets rather than implying that any particular diet, including a vegan diet, is automatically healthier. It addresses the complexity of what constitutes a 'healthier' diet and indicates that many factors, including cost and cultural acceptability, affect dietary choices and health outcomes.


Input: Task: pass the claim using the given text. Claim: Cognitive biases influence decision-making and perception. [SEP] Text: pmid:19593365 View 29. Xia S, Liu J. A belief-based model for characterizing the spread of awareness and its impacts on individuals’ vaccination decisions. J R Soc Interface. 2014;11. View 30. . A Contribution to the of Epidemics. Sci. 1927. 721. View 31. . of Humans: Dynamics and Control. Press; 1991. 32. . An SIS model for cultural trait transmission with conformity bias. Biol. 2013;90: 56–63. pmid:24071632 View 33. Mathematica. Champaign; IL: Inc. , Wolfram Research; 2012. 34. -Jimenez P. Patterns of vaccination acceptance. Med. 1999. 1716. pmid:10574240 View 35. Bauch CT, Bhattacharyya S. Theory and (supplementary material). Salathé M, editor. PLoS Comput Biol. 2012;8: e1002452. pmid:22496631 View 36. Bhattacharyya S, Bauch CT. A game dynamic model for delayer strategies in vaccinating behaviour for pediatric infectious diseases. J Theor Biol. Elsevier; 2010;267: 276–82. pmid:20831873 View 37. . A vaccination game based on public health actions and personal decisions. Ecol Modell. 2011;222: 1651–1655. View 38. . Long-standing influenza vaccination policy is in accord with individual self-interest but not with the utilitarian optimum. . 2007;104: 5692–7. pmid:17369367 View 39. Bauch CT. Imitation dynamics predict vaccinating behaviour. Sci. 2005;272: 1669–75. pmid:16087421 View 40. D’. Vaccinating behaviour and the dynamics of vaccine preventable infections. Modeling the interplay between human behavior and the spread of infectious diseases. Springer Science+New York; 2013. 287. 41. Bauch CT, Bhattacharyya S. Evolutionary game theory and social learning can determine how vaccine scares unfold. PLoS Comput Biol. 2012;8: e1002452. pmid:22496631 View 42. . SVIR epidemic models with vaccination strategies. J Theor Biol. [SEP] Justify:

Output: The text does not provide any information directly related to cognitive biases or their influence on decision-making and perception. Instead, it references various studies focusing on vaccination behaviors and modeling dynamics related to human behavior, which may include decision-making processes but do not explicitly mention cognitive biases. Therefore, the relationship is deemed irrelevant.


Input: Task: corroborate the claim using the given text. Claim: Climate change is causing more extreme weather events worldwide. [SEP] Text: Long-term trends in climate change–related media volume and sentiment: (top left) total climate change tweet volume over time, from 2010 to 2020, (top center) total climate change tweet volume that also contains 3. Volume correlations around major natural disasters: correlations between climate change and natural disaster (left) tweets and (center) news volume around specific major natural disasters in the NOAA dataset and (right) correlations for climate change tweet sentiment ratios (positive/negative tweets) and natural disaster media volume. The red bars in each of the figures represent the average correlations across NOAA natural disaster date ranges (and 1 day on each side). The average correlations before disasters (to the left of the red line) were calculated from values between 30 days and 2 days before the start of every natural disaster. Average correlations after disasters were calculated from values immediately after the start of natural disasters to the specific number of days after a disaster that each bar represents (up to 30 days after the start of a given disaster). View raw image Fig. 4. Climate change media correlation with natural disaster media increases charts, showing the relationship between increases in natural disaster news and tweet volume and corresponding increases in climate change tweet and news volume metrics (percent increases and standard deviations). Blue lines correspond to the relationships overall across the duration of the study’s time interval (2010–20). Green lines represent only the values present within 15 days of specific major natural disasters in the NOAA dataset, and red lines have the narrower time interval of 5 days surrounding specific disasters. Shown are (top) increases in tweet volume, (middle) increases in news 5. Climate change tweet volume local maxima correlation with natural disasters. The relationship between climate change tweet local maxima, defined as being at least 2 standard deviations (SD) above the mean tweet daily average for the specific dates’ month is shown. Standard deviations and means were calculated on a month-to-month basis, as for other analyses. The news volume percentile represents the news volume percentile threshold (calculated on a monthly basis), and the second column represents the proportion of the climate change maxima previously discussed that also have natural disaster news volume above the corresponding percentile in the leftmost column. The linear regression model and scatterplot in the right area of the figure represent the relationship between news volume percentile and the proportion of climate change tweet maximums that fulfill it. [SEP] Justify:

Output: The text corroborates the claim by discussing the correlations between climate change and natural disasters. It references observations of increases in media volume related to climate change during significant weather events, suggesting a relationship between these occurrences. The mention of climate change tweet volume in correlation with natural disaster events supports the assertion that climate change is connected to extreme weather.


Input: Task: contrast the claim using the given text. Claim: A vegan diet is automatically healthier than other diets. [SEP] Text: The lowest diet quality group had an overall diet quality score of 22 out of 100, compared to 62 out of 100 for the highest diet quality group. These 13 different dietary patterns among Australian adults (Table 2) were compared to the recommendations within the Guidelines [26] and the [7], which are described in more detail below. The discussion of results for this paper focused on the average Australian diet, and 5 selected subgroups: the lowest meat, lowest dairy, highest vegetable, highest diet quality and lowest discretionary choices dietary patterns. Benchmark dietary recommendationsAustralian dietary guidelines(ADGs) are designed to promote health and wellbeing in the Australian population. They are built on a food modelling system [29] where a range of dietary patterns were developed that delivered the nutrient requirements set out in the Values [27] for age and gender subgroups in the Australian population. These dietary patterns considered the usual patterns of intake of Australians as well as factors such as chronic disease risk, food culture, social equity, and practicality [29]. The modelling of these dietary patterns was extensive with many variations in dietary patterns included. As a result of the modelling, the ADGuide recommends average daily servings for each of the following five food groups: Fruit, Vegetables, Grains, Lean meats and alternatives, Dairy foods and alternatives. A daily allowance is also provided for discretionary choices and unsaturated fats and oils. Separate recommended daily serving for the five food groups are provided for age and gender subgroups of the population, and for this analysis the recommendations for the 19–50 years age group for male and females were used. The breakdown of food choices within a food group were guided by the original modelling of the ADGs as this was based on usual patterns of eating for Australians. This modelling guided the proportion of total vegetables as starchy and other vegetables; and the breakdown of meat and alternatives as red meat, other animal-based proteins, and legumes for the current analysis. The modelling of the ADGs for this project selected specific foods within a food group, such as the cut of red meat within the red meat allowance, to be as much as possible like the modelling. [SEP] Justify:

Output: The text contrasts the claim by discussing dietary patterns and guidelines in Australia, suggesting that diet quality varies significantly among different dietary patterns without indicating that a vegan diet is categorically healthier. It mentions various dietary groups and scores, indicating that there are multiple factors influencing diet quality rather than implying that any specific diet, including a vegan one, is automatically healthier.


Input: Task: pass the claim using the given text. Claim: Cognitive biases influence decision-making and perception. [SEP] Text: 2008;253: 1–11. pmid:18023819 View 43. Vardavas R, Marcum CS. vaccination behavior via inductive reasoning game. In: Manfredi P, D’Onofrio A, editors. Modeling the interplay between human behavior and the spread of infectious diseases. 2013. 227. 44. Omission bias and pertussis vaccination. Mak. 1994;14: 118–123. View 45. The impact of imitation on vaccination behavior in social contact networks. PLoS Comput Biol. 2012;8: e1002469. pmid:22511859 View 46. Xia S, Liu J. A to Characterizing the Impact of on Individuals’ Making. PLoS One. 2013;8. pmid:23585835 View 47. The impact of imitation on vaccination behavior in social contact networks. PLoS Comput Biol. 2012;8. pmid:22511859 View 48. Campbell E, Salathé M. Complex social contagion makes networks more vulnerable to disease outbreaks. Sci Rep. 2013;3: 1905. pmid:23712758 View 49. . Collective dynamics of “small-world” networks. Nature. 1998;393: 440–2. pmid:9623998 View 50. . Effective vaccination strategies for realistic social networks. its Appl. 2007;386: 780–785. View 51. Perisic A, Bauch C. A simulation analysis to characterize the dynamics of vaccinating behaviour on contact networks. BMC Infect Dis. 2009;9: 77. pmid:19476616 View 52. Perisic A, Bauch CT. Social contact networks and disease eradicability under voluntary vaccination. PLoS Comput Biol. 2009;5: e1000280. pmid:19197342 View 53. Salathé M, Khandelwal S. Assessing vaccination sentiments with online social media: Implications for infectious disease dynamics and control. PLoS Comput Biol. 2011;7. pmid:22022249 View 54. Salathé M, Bonhoeffer S. The effect of opinion clustering on disease outbreaks. J R Soc Interface. 2008;5: 1505–1508. pmid:18713723 View 55. Impact of anti-vaccine movements on pertussis control: The untold story. Lancet. [SEP] Justify:

Output: The text discusses various studies related to vaccination behavior and infectious diseases but does not explicitly mention cognitive biases, their influence on decision-making, or perception. Therefore, it is considered irrelevant to the claim.


Input: Task: corroborate the claim using the given text. Claim: Climate change is causing more extreme weather events worldwide. [SEP] Text: 30 Views 1371 0 0 Views 1120 786 109 PDF Downloads 807 527 74 of Variability on the in Storage over the Tigris–Basin Authors: Li-and Guo-Evaluation of Performance of to Authors:. Yang, Ardeshir Ebtehaj, Sajad Vahedizade, and A 440-of in California from Authors: Ian M. Howard, David W. Stahle, Michael D. Dettinger, Cody Poulsen, F. Martin Ralph, Max C. A. Torbenson, and Quantifying the Role of Variability and from to at in India Authors: Divya Upadhyay, Sudhanshu Dixit, and Rainfall and Flooding from in the Mid-of the Authors: Yibing Su, James A. Smith, and Previous 10. 1175/WCAS-D-22-0053. 1 Page(s): 17–30 1. Ida made landfall on 29 August 2021, bringing sustained winds of 150 mi h−1 (67 m s−1) heavy rainfall, and catastrophic storm surge to the Gulf Coast, before threatening the Northeast with flooding and tornadoes, killing almost 100 people (Hanchey et al. 2021). Natural disasters pose a constant threat of economic damage and lives lost for the United States. In 2021 alone, extreme weather resulted in 688 lives lost, in addition to over USD 145 billion worth of damage. Unfortunately, this toll only continues to rise (Smith 2020). According to the (NOAA), the average yearly cost of natural disaster damage over the past 5 years has reached USD 148. 4 billion, triple that of the 37 years prior (adjusted for inflation) (Smith 2020). Furthermore, a 2012 on (IPCC) report found that extreme weather events will continue to undergo unprecedented changes in frequency, intensity, spatial extent, and duration as a direct result of global warming (IPCC 2012). Nonetheless, according to a 2020 Center poll, only about 60% of Americans feel that climate change is a major threat to the country (Poushter and Fagan 2020). Because of their broad accessibility and widespread popularity in the throughout the past decade, social media platforms represent effective environments in which to study public opinions on climate change. [SEP] Justify:

Output: The text corroborates the claim by providing evidence that extreme weather events have been increasing in frequency and intensity as a direct result of global warming. It cites a 2012 IPCC report that states extreme weather will continue to undergo unprecedented changes due to climate change, thus supporting the assertion that climate change is causing more extreme weather events around the world.


Input: Task: contrast the claim using the given text. Claim: A vegan diet is automatically healthier than other diets. [SEP] Text: Therefore, this modelled version of the ADGs could be described as a dietary pattern that includes more sustainable food choices in amounts recommended by the ADGs. Adaptation of the planetary health diet to the Australian contextprovides daily food intake recommendations for a diet that was designed to “optimise human health and environmental sustainability” as described in the EAT-Lancet report [7]. The diet was designed to meet the WHO global recommendations for all nutrients other than phosphorus and copper where the targets were used [30]. takes a global focus and includes broadly global foods from eight food groups: Fruit, Vegetables, Starchy vegetables/tubers, Wholegrains, Dairy foods, Protein sources (including meat and alternatives), Added fats and Added sugars. The recommendations provide a target based on an average amount, as well as lower and upper boundaries (in grams) for each food group listed. This analysis used the which is based on the average value. In its development, the (PHRD) was modelled using examples of commonly consumed foods in the United States, and the nutrient composition of the diet was originally estimated using the U. S. Department of Agriculture (USDA) Foods Database, Food[31, 32]. In the present study, the PHRD modelled using the USDA database was adapted to the Australian context using foods from the 2011–2013 food composition database [23]. The PHRD was modelled using a single list of 35 food items. Modelling the PHRD with a series of iterations similar to the 2013 ADGs was out of scope for this paper. Rather, individual food items were selected from the database using the food item name and nutrient composition that was considered the closest possible match to the USDA modelled diet [32]. Table 1 for a comparison of foods used in the modelling. In most circumstances there were suitable options in. In circumstances where the USDA modelled diet used higher fat products, such as whole milk and non-lean meat (e. g. beef, ground, 15% fat), lower fat items such as reduced fat milk and low-fat meat (e. g. beef mince < 5% fat) were used to comply with the ADGs recommendations [26]. The PHRD does not contain discretionary foods or beverages like the ADGs, however, the added saturated fats and oils, and added sugar are considered discretionary and were converted to servings of discretionary choices. [SEP] Justify:

Output: The text contrasts the claim by discussing the Planetary Health Diet (PHRD), which includes a variety of food groups, including both plant and animal sources. It highlights that this diet aims to optimize human health and environmental sustainability rather than advocating that a vegan diet is superior in all contexts. By emphasizing the inclusion of 'Protein sources (including meat and alternatives)' and detailing the diverse food composition required for a healthy diet, the text suggests that a vegan diet alone is not necessarily healthier than other dietary patterns.


Input: Task: pass the claim using the given text. Claim: Priming can affect behavior without conscious awareness. [SEP] Text: 753Mean R2 (σ)0. 565 (0. 126)0. 563 (0. 128)0. 555 (0. 129)0. 539 (0. 131) Crucially, however, the ideal observer does exhibit Performance > Awareness (Figure 3G), and to a similar extent as our human participants (R2 = 0. 565; see 0. 025 cycles/pixel, tilted by 45° to the right or the left of vertical. Gratings and subtended 500 pixels, or ~111 visual degrees, and were presented in a circular annulus with a Gaussian hull spatial constant of 100. On each trial, targets could take on one of thirteen possible contrast levels drawn from the range 15–90%. Masks consisted of white noise patches of random RGB values bandpass-filtered to a range of spatial frequencies immediately surrounding the spatial frequency of the target. They were presented in a circular annulus of identical size to the spatial envelope of the Gabor patch targets. All stimuli were displayed via a custom Matlab R2013a (Natuck, MA) script utilizing PsychToolbox 3. 0. 12 on a gamma-corrected Dell E773c CRT monitor with a refresh rate of 75 Hz. Procedure – Experiment 1 Request a detailed protocol Nine subjects participated in Experiment 1. Subjects were seated with their chins in a chinrest at a viewing distance of 42 cm from the screen. Targets and masks (Figure 1A) were presented for two to three frames (33–40 ms) each (jittered timing, with equal probability for two or three frames), with 33-40 ms ISI between masks and 0ms ISI for target-mask or mask-target transitions, in a forward- and backward-masking paradigm in which three masks were presented before and three after the target presentation (i. e. , the target was ‘sandwiched’ between mask presentations) (Figure 1B). The trial structure extends the two-by-two forced-choice (2x2FC) paradigm first introduced by Nachmias and Weber (1975) and subsequently employed to explore the relationship between detection and identification (e. g. , Thomas et al. , 1982; Watson and Robson, 1981), and more recently applied to research on confidence (Barthelmé et al. , 2009, 2010; de Gardelle and Mamassian, 2014). We combined these procedure types. [SEP] Justify:

Output: The text does not address the claim about priming affecting behavior without conscious awareness. Instead, it describes a behavioral experiment involving targets, masks, and a detailed procedural description without explicitly discussing priming or its impact on behavior in relation to awareness.


Input: Task: corroborate the claim using the given text. Claim: Climate change is causing more extreme weather events worldwide. [SEP] Text: Twitter, a robust platform for real-time opinion sharing by experts and nonexperts alike, was specifically chosen for this analysis of public climate change sentiment due to its character limit on posts, enabling sentiment and volume analysis. Given the inextricable connection between extreme weather events and climate change, this study hypothesized that an increase in Twitter posts and news 2. Methods a. (IDE) and Pro were both used for Python development. This study consisted of three main phases: 1) data collection, 2) media volume relationships and correlation analysis, and 3) climate change sentiment analysis. b. Data collection/scraping Twitter posts published publicly in the between 2010 and 2020 were scraped by specific keywords, using the sntwitter module of the snscrape application programming interface (API; Khattak et al. 2020; JustAnotherArchivist 2022). Tweets published prior to 8 November 2017 conform to a 140-character limit, whereas later tweets conform to a 280-character limit. For the purpose of the study, “natural disaster tweets/news” refers to corresponding media collected using the following keywords selected on the basis of the weather events considered to be most linked to climate change: “natural disaster,” “cyclone,” “hurricane,” “tornado,” “wildfire,” “flood,” “tsunami,” and “drought” (Sauerborn and Ebi 2012). Similarly, “climate change tweets/news” refers to corresponding media collected with the specific keywords, “climate change” and “global warming,” given the Twitter audience’s demonstrated lack of differentiation between the two terms (Yeo et al. 2017). “Dual-category tweets/news” refers to climate change media that also contains natural disaster keywords. All data were sourced from the United States. In total, 131 804 385 natural disaster tweets and 34 876 556 climate change tweets were collected and cataloged. All tweets and their associated likes, replies, and retweets were counted and recorded by date. Climate change tweets were saved and further examined for natural disaster keywords. News 2. 6 million unique tweets, with a rough balance of positive and negative sentiment classifications (as opposed to the original disparities in classification totals). [SEP] Justify:

Output: The text supports the claim by discussing the connection between climate change and extreme weather events. It mentions that the study hypothesized an increase in Twitter posts related to natural disasters linked to climate change, indicating a recognition of their correlation. The keywords selected for data collection, such as 'natural disaster,' 'cyclone,' 'hurricane,' 'tornado,' 'wildfire,' 'flood,' 'tsunami,' and 'drought,' further highlight the relationship being investigated between extreme weather events and climate change.


Input: Task: contrast the claim using the given text. Claim: A vegan diet is automatically healthier than other diets. [SEP] Text: The red dashed line represents 100% of the recommendations in the Guidelines or the Reference DietFull size imageThe overall recommendations for meat and alternatives in the PHRD exceeded the ADGs because of the inclusion of 3. 26 servings of plant-based alternatives. The PHRD recommends small amounts of animal-based meat and alternatives, and so the average Australian diet contain more than twice as much animal-based meat and alternatives than the PHRD (258%). Interestingly, the PHRD and the ADGs recommend similar amounts of poultry and seafood. The average Australian diet contained similar amounts of fruit as the PHRD, but almost four times more discretionary foods (5. 57 vs 1. 49 servings, 374%) and about 1. 5 times more dairy and alternatives (1. 55 vs 0. 96 servings, 161%). Despite exceeding the PHRD recommendation, dairy and alternatives consumption of the average Australian diet was below ADGs recommendation (Fig. 1). Composition of selected Australian diets compared to guidelinesDietary patterns within the population can vary substantially, which is not reflected when examining the average pattern. To understand the degree to which various diets within the Australian population aligned with the modelled ADGs diet and the PHRD, we examined selected dietary patterns based on gender, level of consumption of meat and dairy foods, level of consumption of vegetables and discretionary foods, and overall diet quality (2). Figure 2 shows the food group composition of the average Australian diet, as well as the composition of the diets of a subgroup of Australians with the lowest consumption of animal-based meat and dairy foods and compared these to the modelled ADGs diet and the PHRD. A diet that was lowest in animal-based meat contained 1. 09 servings of the meat and alternatives food group. The amount of red meat in this dietary pattern (0. 30 servings) was one third of the average Australian diet (1. 01 servings), and about half of that recommended in the ADGs (0. 70 servings), but twice that recommended in the PHRD (0. 30 vs 0. 15 servings). The amount of other animal-based alternatives (poultry, fish and seafood, eggs) was slightly higher in the PHRD than the lowest meat pattern (0. 63 vs 0. 50 servings) and plant-based alternatives substantially higher (3. 26 vs 0. 30 servings). Fig. [SEP] Justify:

Output: The text contrasts the claim by analyzing the dietary patterns of the Australian population, emphasizing that these patterns can vary significantly. It specifically mentions that the average Australian diet contains more animal-based meat and alternatives than recommended by health guidelines, but also indicates that a diet lower in animal products does not necessarily mean it is automatically healthier. It highlights the need for understanding various diets and their alignment with dietary recommendations, suggesting that being vegan does not inherently guarantee a healthier dietary pattern.


Input: Task: pass the claim using the given text. Claim: Priming can affect behavior without conscious awareness. [SEP] Text: At each contrast level for each subject, we next calculated (a) percent correct orientation discrimination, (b) percent of trials in which the target-present interval was chosen, (c) Type 2 hit rate and Type 2 false alarm rate according to standard Type 2 signal detection theoretic definitions (Type 2 hit: correct orientation discrimination and bet on target-present interval; Type 2 false alarm: incorrect orientation discrimination and bet on target-present interval) (Fleming and Lau, 2014; Maniscalco and Lau, 2012), and (d) percent correct orientation discrimination conditional on having chosen the target-present versus target-absent interval. Group-level analyses and graphical presentation were conducted by binning subjects’ data into ten equally-spaced bins of percent correct orientation discrimination performance in the range 0. 5 – 1 and calculating the mean and standard deviation of each of the above statistics for each bin. To interpolate between discrete data points, we fitted a kernel smoothing regression function to each observer’s data, which is a non-parametric approach to estimate the conditional expectation of a random variable, EYX = fX where f is a non-parametric function. This approach is based on kernel density estimation, implementing Nadaraya-Watson kernel regression (Nadaraya, 1964; Watson, 1964) via (1) f^x;K,h = ∑i=1nKhx-xiyi∑i=1nKhx-xi where K is a Gaussian kernel with bandwidth h. All analyses were carried out in Matlab R2013a (Natuck, MA) and SPSS Version 22 (IBM Corporation; Armonk, NY). Bayesian ideal observer model Model space Request a detailed protocol Our model representation space extends Macmillan and Creelman’s (2004) two-dimensional signal detection theory (SDT) and related Bayesian (King and Dehaene, 2014) framework, in which stimulus categories are represented by bivariate Gaussian distributions centered along the axes in a Cartesian plane, and ‘noise’ (or a blank stimulus) is represented by a similar bivariate Gaussian centered at the origin (Figure 4). Although for this particular task we could have used a 1-dimensional space alternative (see e. g. Sridharan et al. , 2014), to facilitate additional model variants (see 10. [SEP] Justify:

Output: The text does not address the claim regarding priming and its effects on behavior without conscious awareness. Instead, it focuses on statistical analyses and model representations related to orientation discrimination and signal detection theory, which are unrelated to the concept of priming.


Input: Task: corroborate the claim using the given text. Claim: Climate change is causing more extreme weather events worldwide. [SEP] Text: 2) Major natural disasters from NOAA dataset overview metrics A total of 122 individual events (with a combined toll of USD 762 billion in damage and 5000 lives lost) between 2010 and 2020 from the NOAA dataset were used for these analyses. On average, each catastrophe cost approximately USD 6. 25 billion and killed 40 people. However, median values were significantly lower, at USD 2 billion in damage cost and 3 deaths, suggesting a right skew caused by a select few notable events. A3 of the 1. 93% to 3. 97% for all tweets, and from 2. 0% to 4. 3% for popular tweets, suggesting that public awareness of the relationship between climate change and extreme weather events effectively doubled during the 11-yr study period (Table 1). A similar trend is evident in the number of news 2. Long-term trends in climate change–related media volume and sentiment: (top left) total climate change tweet volume over time, from 2010 to 2020, (top center) total climate change tweet volume that also contains 10. 1175/WCAS-D-22-0053. 1Download FigureDownload figure as PowerPoint slide 2) Volume and sentiment changes around major natural disasters On average, climate change tweet volume increased approximately 4% between the start dates of each natural disaster and the baseline 15 days prior to the event (Table 2). The end date and daily mean increases from the baseline during disasters were 11. 70% and 9. 15%, respectively, while the peak climate change tweet volume during major natural disasters demonstrated a 32. 47% increase from the baseline, on average. These climate change tweet volume increases were significantly higher for events that fell in Q4 of natural disasters tweet volume at 21. 45%, 21. 67%, 24. 16%, and 50. 68% for the start date, end date, daily average, and peak volumes inside events’ date ranges, respectively. Similarly, the number of dual-category tweets rose on average 31. 24%, 69. 21%, and 49. 95% for the start, end, and daily averages for each date range. Events in Q4 of natural disasters tweet volume once again amplified results with dual-category tweets increasing by 102. 31%, 162. 31%, and 164. 02% for the start date, end date, and daily average volumes. Dual-category tweet peak mean increases were 115. [SEP] Justify:

Output: The text corroborates the claim by discussing data from the NOAA dataset, detailing a significant number of major natural disasters and the increase in public awareness about the connection between climate change and extreme weather events. Specifically, it mentions how the volume of tweets related to climate change significantly increased around the times of major natural disasters, suggesting a heightened public recognition of the relationship between these disasters and climate change. This aligns with the claim that climate change is causing more extreme weather events.


Input: Task: contrast the claim using the given text. Claim: A vegan diet is automatically healthier than other diets. [SEP] Text: 3Daily average food group intake (servings per day) of selected Australian adults aged 19–50 years stratified by indicators of a healthy diet (highest vegetables, diet quality and lowest discretionary choices) and compared to the Guidelines and the Reference Diet. Values are presented as meansFull size imageBecause diet quality was operationalised as compliance with ADGs, the food group consumption of the subgroup of the population with the highest diet quality was most closely aligned with this set of guidelines. The diets of this subgroup still consumed less vegetables (3. 92 vs 5. 50 servings) and less dairy and alternatives (1. 71 vs 2. 50 servings) than the modelled ADGs. None of the dietary patterns of the subgroups examined in this analysis consumed cereals, plant-based meat alternatives to meat (legumes and nuts) and unsaturated fats in amounts close to the recommendations in the PHRD. Types of meat and alternatives within selected dietary patternsFigure 4 shows the breakdown of the types of meat and alternatives as a proportion of total servings. Typically, in Australian diets, irrespective of the amount of meat, vegetables, discretionary foods, or overall quality, the proportion of total meat and alternatives consumed as red meat was between 28 and 44%, and for poultry between 25 and 32% of the total meat and alternatives This compared to 25% red meat and 8% poultry in the modelled ADGs, and 4% red meat and 6% poultry in the PHRD. It is recommended that when following the PHRD, most servings (around 80%) selected from the meat and alternatives food group should be plant-based, such as legumes and nuts. diets, the subgroup with the lowest meat consumption had the highest proportion as plant-based alternatives (27%), followed by those with the highest diet quality (18%) and highest vegetable consumption (18%). Proportionally, fish and seafood contributed similar amounts to total meat and alternatives in the and average Australian diet (~ 7–8%). Fig. 4Daily average consumption of red meat, animal-based alternatives (broken down into subcategories of poultry, fish and seafood, eggs) and plant-based alternatives (legumes, tofu and nuts and seeds) as a percentage of total meat and alternatives and compared to the Guidelines modelled diet and the Reference Diet. Values are presented as a percentage. [SEP] Justify:

Output: The text contrasts the claim by providing detailed analysis of dietary patterns, showing that even the subgroup with the highest diet quality in the study consumed less vegetables and dairy than recommended. It indicates that the inclusion of plant-based alternatives is recommended, yet does not automatically imply that a vegan diet is healthier than all other diets, especially when the participants' adherence to dietary guidelines is critiqued.