Input: Task: contrast the claim using the given text. Claim: AI can replace doctors entirely for all diagnostic and treatment decisions. [SEP] Text: Quantitative VD, however, has a number of limitations in the high surgical risk and TAVI population. The assessment requires additional intraprocedural time to determine the OPA, a specific injection protocol that necessarily increases the contrast burden in each case, and fails to discriminate transvalvular regurgitation from PVR – important in determining the appropriate intraprocedural treatment following TAVI (i. e. , post-dilatation or valve-in-valve). Intraprocedural haemodynamics have also been used13,14 but similarly suffer from the dependence on heart rate, an inability to distinguish central from paravalvular regurgitation and, in addition, significant overlap of mild and moderate PVR grades, the latter grade being associated with an increase in mortality post TAVI15. Echocardiography thus remains the preferred method for assessing PVR, since this imaging modality can identify the location (including central versus paravalvular), number and size of the PVR jets, and provide a multi-parametric assessment in a continuous, physiologic manner. Although a 5-grade scheme has been proposed for research protocols16, this scheme can be reduced to the typical 3-grade scale advocated by the guidelines (Table 1). Whereas grading of surgical or transcatheter AR is similarly multi-window and multi-parametric, grading of PVR following TAVI has important caveats9: 1. Circumferential extent should be assessed as the sum of the individual small jets and not the arc that includes non-regurgitant spaces due to the stent frame or calcific leaflets. To assess the jet number and regurgitant orifice location and size accurately, meticulous scanning is required to identify the origin of the jets and confirm their path into the LVOT. 2. Given the frequent presence of ventricular and aortic compliance abnormalities in this patient population, mitral E:A ratio, pressure half-time and holodiastolic reversal of flow in the descending aorta should be used with caution in isolation but may have utility when comparing a baseline to a post-TAVI flow pattern. 3. Jet length or jet area should not be used to assess the severity of AR following TAVI since these jets are frequently eccentrically directed, constrained by the LVOT, or entrained within the LVOT, leading to rapid jet broadening. 4. [SEP] Justify:

Output: The text contrasts the claim by highlighting the limitations of current quantitative methods, such as the need for meticulous scanning and the critical nature of echocardiography in assessing patient conditions like PVR after TAVI. It indicates that the complexity of surgical assessments and the necessity for specialized physician skills suggest that AI alone cannot fulfill the role of doctors in making all diagnostic and treatment decisions.


Input: Task: pass the claim using the given text. Claim: Certain researchers argue that the properties of proteins can predict their functions accurately. [SEP] Text: Competing interests: The authors have declared that no competing interests exist. Abbreviations: FDA, Food and Drug Administration; RP:CB, Reproducibility Project: IntroductionApproximately 90% of new drugs entered into clinical development on promising preclinical findings fail to yield sufficient efficacy and safety to receive a Food and (FDA) license [1]. Such high rates of discordance between preclinical reports and clinical effects have prompted mounting scrutiny of the design, reporting, and reproducibility of preclinical research. Being unable to reproduce preclinical findings can impede medical progress and misallocate intellectual capital. For example, laboratories attempting to reproduce original findings might squander limited research resources because they are not attuned to subtle techniques needed to reproduce an original finding. Of even greater concern is the prospect of launching clinical investigations on the backs of invalid preclinical reports. Scientists’ judgments about an experiment’s reproducibility influence how they go about designing similar studies, as well as which findings are utilized for the design of subsequent studies. Accurate judgment about reproducibility therefore affects how efficiently science self-corrects. There is widespread debate about the scope of the reproducibility problem in many scientific fields, including biomedical research. Most scientists (52%) think there is a “significant” reproducibility crisis, whereas the remainder think there is, at worst, a “slight” crisis [2]. Some direct efforts at reproducing preclinical and basic science findings have suggested that many original findings may be spurious. For example, researchers at Amgen were unable to reproduce 89% of cancer preclinical studies provided to them by academic scientists; similar challenges were reported by Bayer scientists [3]. However, community-wide beliefs are somewhat measured, since 31% of researchers believe a result still might be true even in light of a failed replication attempt [2]. Indeed, many commentators have questioned the efforts and expertise of those conducting replication studies [4,5]. Uncertainty about the extent, causes, and impact of the “reproducibility crisis” has led to calls for more systematic assessments of the problem [6]. Project: (RP:CB) is currently conducting 29 direct replication studies to evaluate the replication rate in cancer biology [7]. By collecting subjective probability forecasts on outcomes that can be unambiguously dichotomized, one can score the accuracy of individuals’ strength of belief using well-established methods from the decision sciences [8]. [SEP] Justify:

Output: The text is irrelevant to the claim as it focuses on the reproducibility crisis in preclinical research and the challenges faced in reproducing scientific findings. It does not provide any information or arguments related to whether the properties of proteins can predict their functions.


Input: Task: corroborate the claim using the given text. Claim: Certain animal species are keystone species, influencing entire ecosystems. # factual [SEP] Text: The red swamp crayfish Procambarus clarkii in Europe: Impacts on aquatic ecosystems and human well-being. Limnologica 58: 78–93. [1973. Crayfish in Austria, history and actual situation. 1: 10–14. [2000. Crayfish as geomorphic agents and ecosystem engineers: Biological behavior affects sand and gravel erosion in experimental streams. 45: 1030–1040. [CrossRef] [2002. Riverine flood plains: Present state and future trends. 29: 308–330. [CrossRef] [2014. Distribution and current status of stone crayfish populations Austropotamobius torrentium (Decapoda: Astacidae) in Natura 2000 protected areas in Bulgaria. Bulg 66: 181–202. [2020. Faxonius limosus (Rafinesque, 1817) (Decapoda: Cambaridae), a new invasive alien species of European union concern in Bulgaria. Bulg 72: 113–121. [2019. Impact of floods on increased heavy metal content in the inundation area of the Drava river in the Varaždin county. Hrvatske vode 5: 305–316. [2013. Freshwater crayfish (Decapoda: Astacidae) distribution and conservation in Bulgaria. 19: 243–248. [2005. Phylogenetic and phylogeographic relationships in the crayfish genus Austropotamobius inferred from mitochondrial COI gene sequences. Evol 34: 212–226. [2011. Freshwater crayfish in Bosnia and Herzegovina: the first report on their distribution. Knowl. Manag. Aquat. Ecosyst. 401: 26. [CrossRef] [EDP Sciences] [2013. A global meta-analysis of the ecological impacts of nonnative crayfish. 32: 1367–1382. [2012. Mura-Drava-. [2000. Effects of crayfish on leaf processing and invertebrate colonisation of leaves in a headwater stream: decoupling of a trophic cascade. Oecologia 124: 608–614. [CrossRef] [PubMed] [1999. Stable isotope evidence for food web consequences of species invasions in lakes. Nature 401: 464–467. [SEP] Justify:

Output: The text corroborates the claim by discussing various studies related to crayfish, specifically mentioning their roles in aquatic ecosystems as ecosystem engineers and geomorphic agents. The mention of impacts on leaf processing, invertebrate colonization, and the ecological consequences of species invasions supports the idea that certain animal species, such as crayfish, are keystone species that can significantly influence their ecosystems.


Input: Task: contrast the claim using the given text. Claim: All healthcare facilities worldwide are equipped to use AI systems effectively. [SEP] Text: Policy: ASTM International prohibits the entry of ASTM standards and related ASTM intellectual property (“”) into any form of (AI) tools, such as ChatGPT. Additionally, creating ----derivatives of using AI is also prohibited without express written permission from ASTM’s President. In the case of such use, ASTM will suspend a licensee’s access to and further legal action will be considered. Meetings & | Meetings & & & Standards and Papers & STPs Manuals, Monographs, & of ® (SOP) (TMA) and & & & & and ASTM What is and to to News and & -11. 03 Committee F23 $ 83. 00 In stock AbstractThis specification establishes the requirements for the performance, documentation, and labeling of surgical gowns used in the healthcare facilities. It does not however cover all the requirements that a healthcare facility deems necessary to select a product, nor does it address criteria for evaluating experimental products. Barrier testing shall be conducted to determine the impact penetration, hydrostatic resistance, and viral penetration resistance performance of the critical zone(s) of the surgical gown. The physical properties of the critical zone(s) of the surgical gown shall also be tested and shall conform to the following requirements: tensile strength, tear resistance, seam strength, lint generation, evaporative resistance, and water vapor transmission rate. General safety requirements shall be set based on biocompatibility, sterility assurance, flame spread, and natural rubber latex specifications. Scope1. 1 This specification establishes requirements for the performance, documentation, and labeling of surgical gowns used in the healthcare facilities. Four levels of barrier properties for surgical gowns are specified in 70:2003 and are included in this specification for reference purposes. Note 1Some properties require minimum performance and others are for documentation only. Note 270:2003 evaluates the barrier properties of surgical gown fabrics using water only in Levels 1, 2, and 3. Since surgical gowns are exposed to blood and other fluids with different surface tensions, the performance of additional testing to identify the barrier levels to simulated biological fluids is required for a Level 4 gown. 1. 2 This specification does not cover all the requirements that a healthcare facility deems necessary to select a product, nor does it address criteria for evaluating experimental products. 1. [SEP] Justify:

Output: The text contrasts the claim by highlighting the limitations regarding the use of AI tools in healthcare as established by ASTM International. It specifies that standards and related intellectual property cannot be integrated into AI tools without proper permission, which indicates that not all healthcare facilities have the necessary infrastructure or permission to effectively use AI systems.


Input: Task: pass the claim using the given text. Claim: Certain researchers argue that the properties of proteins can predict their functions accurately. [SEP] Text: For example, in a study examining economists’ predictive judgments about replication studies, forecasts significantly correlated with replication results and beat a matched prediction market about the same replication studies [9]. In contrast, psychologists’ forecasts did not significantly correlate with replication results, and their forecasts were beaten by a similar, matched prediction market [10]. Here, we report forecasts and their accuracy for the first 6 mouse-model replication studies conducted by the RP:CB. We set out primarily to determine the extent to which expert cancer researchers can accurately predict the probability of replicating significance levels and effect sizes from specific original studies in the RP:CB. We close by discussing our findings in light of the many complexities of conducting and interpreting replication studies, including the particular experiments used in our surveys. demographics We recruited a sample of 196 participants, including 138 experts and 58 novices, to perform forecasts for our study (Table 1 summarizes the sample demographics). Experts were predominantly male, whereas there were slightly more female than male novices. Our expert sample showed a somewhat lower mean h-index compared with nonresponders (25. 6 versus 32. 4)—based on an equally sized random sample of nonresponders. Download: PPTPowerPoint slidePNGlarger imageTIFForiginal imageTable 1. Sample demographics by rank of participants. average expert had published 89. 5 (SD = 109. 0) papers and been cited 4,546. 1 (SD = 7,932. 4) times. A third of the sample (27% of experts and 44% of novices) had not heard of the RP:CB, while 9% (10% of experts and 7% of novices) were actively awaiting results. The expert sample believed they had reasonable expertise pertaining to the studies in our survey. The mean expertise rating was 4. 2 (SD = 1. 9) on a 7-point scale (with 1 representing minimal expertise and 7 representing maximal expertise). A plurality of expert participants (45%) rated their expertise above the scale’s midpoint, and 33% below the midpoint. The mean expertise rating for the novices was 2. 9 (SD = 1. 5), with only 15% of novice expertise ratings above the midpoint and 65% below. Both the experts and novices rated high confidence in their forecasts, 77% versus 76% respectively. [SEP] Justify:

Output: The text is irrelevant to the claim as it discusses the predictive judgments of economists and psychologists regarding replication studies in a different context. There is no mention of proteins or their properties, nor any indication that the text addresses the topic of predicting functions based on properties of proteins.


Input: Task: corroborate the claim using the given text. Claim: Certain animal species are keystone species, influencing entire ecosystems. # factual [SEP] Text: [CrossRef] [2021. Trophic niches of three sympatric invasive crayfish of EU concern. Hydrobiologia 5: 727–737. [CrossRef] [2009. The continuing spread of Pacifastacus leniusculus in Carinthia (Austria). Knowl. Manag. Aquat. Ecosyst. 394–395: 17. [CrossRef] [EDP Sciences] [2010. The ecology and habitat requirements of Austropotamobius torrentium in small forest streams in Carinthia (Austria). 17: 221–226. [2016. Native and alien crayfish species: Do their trophic roles differ? 35: 1340–1353. [CrossRef] [2014. Landscape analyses offer a promising tool for managing native and alien crayfish species. 20: 27–40. [CrossRef] [2020. Hungary: A European hotspot of non-native crayfish biodiversity. Knowl. Manag. Aquat. Ecosyst. 421: 43. [CrossRef] [EDP Sciences] [2018. Species in Balkan Rivers: their distributions and threats from hydropower development. 162 p. [2021. World’s first 5-country biosphere reserve will benefit people and nature in the ‘Amazon of. [2013. Assessment of the River and Potential in the “Mura-Drava-Danube”, WWF, Vienna. [2020. The spiny-cheek crayfish Faxonius limosus (Rafinesque, 1817) (Decapoda: Cambaridae) invades new areas in Serbian inland waters. Bulg 72: 623–627. [2022. Overlooked keystone species in conservation plans of fluvial ecosystems in Southeast Europe: a review of native freshwater crayfish species. Knowl. Manag. Aquat. Ecosyst. , 423, 21. Fig. 1Freshwaters in SEE with watershed of the basin marked with red line, produced in QGIS v. 3. 16. 10. [SEP] Justify:

Output: The text corroborates the claim by discussing the importance of certain species, specifically native freshwater crayfish, in the context of conservation plans for fluvial ecosystems. It highlights the role of these species as potential keystone species, which supports the claim regarding their influence in ecosystems.


Input: Task: contrast the claim using the given text. Claim: All healthcare facilities worldwide are equipped to use AI systems effectively. [SEP] Text: Policy: ASTM International prohibits the entry of ASTM standards and related ASTM intellectual property (“”) into any form of (AI) tools, such as ChatGPT. Additionally, creating ----derivatives of using AI is also prohibited without express written permission from ASTM’s President. In the case of such use, ASTM will suspend a licensee’s access to and further legal action will be considered. Meetings & | Meetings & & & Standards and Papers & STPs Manuals, Monographs, & of ® (SOP) (TMA) and & & & & and ASTM What is and to to News and & -11. 03 Committee F23 $ 91. 00 In stock and Use 4. 1 This specification provides minimum requirements for surgical gowns used for protection of healthcare workers where the potential for exposure to blood, body fluids, and other potentially infectious materials exists. The specification requires barrier testing based on the system of classifying gowns established in ANSI/70 and sets general safety requirements for surgical gowns based on biocompatibility, sterility assurance, and flame spread. Performance requirements are established for important physical properties, including tensile strength, tear strength, and seam strength. Methods to be used for optional reporting of performance of linting resistance, evaporative resistance, water vapor transmission rate, and abrasion resistance are provided. 4. 2 This specification does not address protective clothing used for nonsurgical applications, such as isolation gowns or decontamination gowns; protective clothing for the hands, such as surgical gloves, patient examination gloves, or other medical gloves; protective clothing for the head, such as goggles or face shields, surgical caps or hoods, surgical masks, or respirators; protective clothing for the feet, such as operating room shoes, shoe covers, or surgical boots; or other types of protective clothing and equipment worn by healthcare providers. 4. 3 Surgical gowns are either multiple-use or single-use products as designated by the manufacturer. This specification is intended to provide the basis for manufacturer claims for surgical gown performance and efficacy. For multiple-use gowns, this specification takes into account the anticipated care and maintenance of these products by examining test requirements for surgical gown materials both before and after the maximum expected number of cycles for laundering and sterilization. 4. 4 Additional information on the processing of multiple-use surgical gowns is provided in ANSI/65. [SEP] Justify:

Output: The text contrasts the claim by discussing specific ASTM standards and requirements for surgical gowns and protective clothing. It indicates that there are structured regulations and prohibitions regarding the use of AI in this context, as stated in 'ASTM International prohibits the entry of ASTM standards and related ASTM intellectual property into any form of (AI) tools.' This suggests that not all healthcare facilities are free to implement AI systems, as such usage is regulated and may not be allowed, thereby contradicting the claim that they are all equipped to use AI effectively.


Input: Task: pass the claim using the given text. Claim: Certain researchers argue that the properties of proteins can predict their functions accurately. [SEP] Text: For both groups, 84% of confidence ratings were above 50%, and only 3% were below. Table 2 shows the publications used in this forecasting study and summaries of forecasts for each [11–16]. Disease indications in xenograft studies included prostate, lung, renal cell, and breast cancer, as well as myeloma, leukemia, and melanoma, and the experiments used a variety of outcome measures, including disease-free survival, tumor weight and volume, organic phase absorbance, and bioluminescence. Studies were preselected by the RP:CB using a standardized search method [7]. Download: PPTPowerPoint slidePNGlarger imageTIFForiginal imageTable 2. Study 10. 1371/journal. pbio. 2002212. t002 Forecast properties Experts used the whole spectrum of belief (see Fig 1). They tended to believe replication studies would demonstrate statistical significance, since 73% of forecasts were above 50%, and 49% were above 75%. Only 18% of forecasts were below 50%. In contrast, experts gave lower forecasts (centered near 50%) for effect size, with forecast patterns suggesting community uncertainty (median forecast of 50% for 4 studies and the other 2 suggesting doubt (median forecasts of 25% and 40%). Download: PPTPowerPoint slidePNGlarger imageTIFForiginal imageFig 1. Expert forecasts by identified expertise and by study. The gray histogram represents the forecasts of significance (panel A) and effect size (panel B) with bins of 5%. A 100% forecast and a 0% forecast would indicate certainty that an event will occur and will not occur, respectively; 50% would indicate maximum uncertainty. The red lines represent forecasts for the studies in which each forecaster was identified during sampling via either 10. 1371/journal. pbio. 2002212. g001Our question about effect sizes could be interpreted differently, resulting in high variability in forecasts. To corroborate interpretation of effect size forecasts, we asked forecasters the likelihood of a perfect replication study producing effect sizes as large or larger than the original, if an original finding were reproducible. We then compared these figures with an individual’s forecasts (see S3 Fig in the Supporting Information). [SEP] Justify:

Output: The text does not address the claim regarding the relationship between protein properties and their functions. Instead, it discusses the confidence levels of experts in forecasting statistical significance and effect sizes in replication studies, while mentioning a variety of diseases and experimental outcomes. Therefore, it is deemed irrelevant to the claim.


Input: Task: corroborate the claim using the given text. Claim: Organic farming often relies on natural fertilizers like compost and manure rather than synthetic chemicals. [SEP] Text: Published print: 01 Feb 2012 AbstractOrganic sweet corn (Zea mays) production is challenging for growers because of the high nitrogen (N) requirements of sweet corn and the relatively low N content of organic soil amendments. supplied and rate of mineralization throughout the growing season are two important aspects in determining the optimal N management program. Green manure (GrM) crops, composted manures, and commercially available organic fertilizers are used to manage N in organic production systems. Using a combination of these tactics can optimize N while minimizing cost. In this study, we used combinations of composted poultry manure (CPM) and two organic fertilizers (one high N and one with a balance of nutrients) with three GrM crops [rye (Secale cereale), alfalfa (Medicago sativa), and pea (Pisum sativum)] in a loamy sand soil for a 112-day laboratory incubation study. Total plant available N (PAN) was quantified at six times throughout the 16 weeks to determine total N mineralized and rate of N release from each of the management programs. The CPM and the high N organic fertilizer mineralized completely within the first 6 weeks of the study, while only 65% of the other organic fertilizer mineralized by the end of the study. mineralized from pea grown as a GrM for 48 days was comparable to the amount of N mineralized from rye suggesting that pea as a GrM crop should not receive an N credit in field production on a sandy soil. Significant quantities of PAN were mineralized from alfalfa residue, the equivalent of 80 lb/acre, although this is not sufficient for sweet corn production. The combination of alfalfa and the high N organic fertilizer provided sufficient N for sweet corn production and the mineralization rate closely matched sweet corn need. The release of N from CPM, even in combination with GrM crops, was asynchronous with sweet corn crop need. Keywords: alfalfa; pea; ryeNitrogen management for optimal crop production is one of the most difficult and costly practices in organic agriculture. The majority of the N in organic sources is bound in organic compounds, which must be mineralized by the soil microbial community to become a PAN form (ammonium or nitrate). Moisture, temperature, and composition of the soil microbe community can affect the rate at which organic N is mineralized. [SEP] Justify:

Output: The text corroborates the claim by discussing the management of nitrogen (N) in organic farming, specifically noting the use of 'composted manures' and 'commercially available organic fertilizers', which are natural fertilizers, in organic production systems. It explains how these organic sources contribute to fulfilling the nitrogen needs for specific crops, hence supporting the idea that organic farming relies on natural rather than synthetic fertilizers.


Input: Task: pass the claim using the given text. Claim: All healthcare facilities worldwide are equipped to use AI systems effectively. [SEP] Text: (f) Licensee will provide ASTM with a list of authorized IP (numeric IP domain addresses) addresses and, if Multi-Site, a list of authorized sites. B. Prohibited Uses. (i) describes all permitted uses. Any other use is prohibited, is a violation of this Agreement and can result in immediate termination of this License. (ii) User may not make this Product, or Documents, available to anyone other than another Authorized User, whether by Internet link, or by permitting access through his or her terminal or computer; or by other similar or dissimilar means or arrangements. (iii) Specifically, no one is authorized to transmit, copy, or distribute any Document in any manner or for any purpose except as described in Section 3 of this License, without ASTM's prior express written permission. In particular, except as described in Section 3, no one may, without the prior express written permission of ASTM: (a) distribute or forward a copy (electronic or otherwise) of any 4. Detection of Prohibited Uses. A. Licensee is responsible for taking reasonable measures to prevent prohibited uses, and promptly notify ASTM of any infringements of copyright or prohibited use of which Licensee becomes aware. Licensee will cooperate with ASTM in investigating any such prohibited uses and will take reasonable steps to ensure the cessation of such activity and to prevent any reoccurrence. B. Licensee shall use all reasonable efforts to protect the Product from any use that is not permitted under this Agreement, and shall notify ASTM of any use of which it learns or is notified. 5. to Product. ASTM reserves the right to terminate this License, upon written notice, if Licensee materially breaches the terms of this Agreement. fails to pay ASTM any license or subscription fees when due, ASTM will provide the Licensee with a 30-day period within which to cure such breach. No cure period will be provided for material breaches relating to violations of Section 3 or any other breach likely to cause ASTM irreparable harm. If Licensee's subscription to an ASTM Product terminates, further access to the online database will be denied. or materially breach this License or make prohibited uses of material in any reserves the right to deny Licensee any access to the ASTM Product, in ASTM's sole discretion. 6. and Service. A. use standard Internet HTML format. [SEP] Justify:

Output: The text is irrelevant to the claim as it discusses licensing agreements and the responsibilities of a licensee regarding the use of products under a specific agreement. There is no mention of healthcare facilities or AI systems, hence it does not support or contrast the claim.


Input: Task: pass the claim using the given text. Claim: Certain researchers argue that the properties of proteins can predict their functions accurately. [SEP] Text: Factors associated with greater forecasting skill A possible explanation for low Brier scores is that forecasters might have lacked expertise in the specific studies in our sample. We probed the relationship between expertise and forecasting skill in several ways. First, we tested whether forecasters performed better on the studies for which we had identified them as experts. Forecasts with identified expertise were more likely to use high extreme values (63% of forecasts were ≥ 75% compared to 51% with general expertise, a difference of 12%, 95% CI [0. 02 to 0. 22]) and less likely to give forecasts near the low extreme (8% of forecasts were ≤ 25% compared to 15% with general expertise, a difference of 7%, 95% CI [−0. 13 to −0. 002]), suggesting greater optimism about reproducibility in one’s own research area. The mean Brier score for significance forecasts was marginally greater for identified expertise (0. 61, 95% CI [0. 54 to 0. 66]) than for general expertise (0. 52, 95% CI [0. 49 to 0. 58] for a mean difference of 0. 09, 95% CI [−0. 01 to 0. 15]). Effect-size forecasts centered around 50% (in terms of median and mode) for both identified and general expertise. Forecasts from general expertise were more likely to use extreme low values: 36% of forecasts in the lowest quartile compared to 27% for identified expertise (a difference of 9%, 95% CI [−0. 01 to 0. 18]). Experts performed better when they were not identified as having expertise, possibly indicating that experts are overconfident when they are more knowledgeable and/or more doubtful about others’ research. A second way we probed the relationship between expertise and forecasting skill was by comparing experts to a sample of trainees in competitive molecular biology programs. We reasoned that if experts outperformed novices, then forecasting success is associated with expertise; if novices outperformed experts, then there is evidence that expertise is associated with overconfidence. We observed the same general patterns of (a) optimism for significance forecasts and (b) uncertainty for effect-size forecasts (centered around a mode of 50%) with a pessimistic leaning (a local mode at 10%) (see S2 Fig in the for a comparison of expert and novice forecasts). [SEP] Justify:

Output: The text is irrelevant to the claim, as it discusses forecasting skill and the relationship between expertise and performance, without addressing the predictive capabilities of protein properties or any connection to functions. The text does not mention proteins or their functions at all.


Input: Task: corroborate the claim using the given text. Claim: Organic farming often relies on natural fertilizers like compost and manure rather than synthetic chemicals. [SEP] Text: content of organic sources is often not completely mineralized within one growing season (Crew and Peoples, 2005; Hartz et al. , 2000; Hartz and Johnstone, 2006). Insufficient PAN in the soil during periods of high crop need can translate into crop deficiency and potentially yield loss. However, excessive PAN in the soil before crop need or at times of low crop N use can leave the nitrate portion susceptible to leaching and inefficient crop use. Ideally, the mineralization rate would match fluctuations in crop need throughout the growing season. Understanding total N contribution and mineralization rate of organic N inputs can allow a comparison with crop need. management is particularly challenging for high N-requiring crops such as sweet corn. Organic growers typically use a variety of strategies to meet crop N needs such as using N-fixing legumes as GrM crops, composted manure, and commercially available amendments (Gaskell and Smith, 2007). Composted manure is a cost-effective means of providing N to an organic crop because of its role as a waste product and relative abundance. However, composted manure presents several challenges for organic sweet corn production. It generally has low N concentration (<5%), so large quantities must be applied (Berry et al. , 2002), adding expense in application. of pest management guidelines suggest that manure also should be applied and incorporated at least 1 week in advance of sweet corn planting to reduce seed damage by seed corn maggot [Delia platura (Boerboom et al. , 2011)]. Sweet corn does not begin to take up significant quantities of N until the five-leaf stage (Doerge et al. , 1991), which can take up to 1 month after planting in the upper midwestern United States. that is mineralized from the manure during this time is vulnerable to loss from leaching or volatilization. Soil amendments that contain higher concentrations of N such as feather meal, bone meal, fish powder, and guano are available commercially in various formulations. Smaller total quantities of these amendments can be applied as they have higher N concentration, ranging 11% to 14% (Hartz and Johnstone, 2006), reducing transportation and application costs compared with manure. Hadas and Kautsky (1994) reported continuous release of PAN from feather meal in an 8-week incubation study. [SEP] Justify:

Output: The text corroborates the claim by discussing the use of composted manure as a strategy for organic growers to meet nitrogen (N) needs for crops. It mentions that organic growers typically employ various methods such as using N-fixing legumes and composted manure, which are consistent with the claim that organic farming relies on natural fertilizers.


Input: Task: contrast the claim using the given text. Claim: AI can predict and prevent all health issues before they occur. [SEP] Text: Fire trackers: how can we use modelling techniques to predict where wildfires will occur? Published: February 14, 2023 Climate change is making many parts of the world hotter and drier. As a result, wildfires are becoming increasingly prevalent and pose a serious threat to human life, local communities and natural ecosystems. Researchers from the at of Melbourne in Australia are developing models that can help predict where wildfires are most likely to occur and how fires behave under different weather conditions. Their research explores how fire management can be used to reduce the risk of damage to human values while maintaining or improving environmental values in the landscape. or Wildfire — an unplanned fire that burns through large areas of scrub or forest Variable heat flux — a measure of how quickly heat energy moves through or across a material Prescribed burns — the controlled application of fire, also referred to as ‘controlled burns’, ‘hazard reduction burns’ or ‘planned burns’. This type of fire is deliberately applied to a pre-determined area at the time, intensity and rate of spread required to achieve the desired management objectives, and occurs under a strict set of environmental conditions Fire suppression techniques — the various strategies for stopping a fire once it has started. These include: spraying a fire with large volumes of water or fire retardant (from the ground or through aerial attack); creating fuel breaks (areas cleared of vegetation by heavy machinery) to stop fire spread or provide safer places for fire fighters to work from; back-burning to reduce or remove fuel/vegetation in strategic areas (e. g. in areas where a fire is predicted to travel) Fuel management — management aimed at reducing connectedness within and between different layers of fuel, by increasing the gap to the canopy to reduce the likelihood of fire reaching the upper layer of fuel, and removing bark to reduce spotting During Australia’s “Black Summer” bushfire season of 2019-20, an area the size of the UK was impacted by bushfires. Tragically, more than 30 people lost their lives as a direct result of these fires, and over 3000 homes were destroyed. It is estimated that over a billion animals perished in these fires and that some species may even have been driven to extinction. The total economic cost of the fires has been calculated at around $80 billion, making them the most costly natural disaster in Australia’s history. [SEP] Justify:

Output: The text contrasts the claim by discussing how modeling techniques can predict wildfires, but does not mention AI being able to predict or prevent health issues. It focuses on predicting fire behavior and management strategies rather than applying similar predictions to health problems, thus demonstrating that the claim about AI's capabilities in health is not supported.


Input: Task: pass the claim using the given text. Claim: Certain researchers argue that the properties of proteins can predict their functions accurately. [SEP] Text: Overall performance did not favor either group: experts slightly outperformed novices in accuracy (median Brier = 0. 32 versus 0. 35), but novices slightly outperformed experts in specificity (0. 45 versus 0. 43). Experts’ significance forecasts were significantly more accurate (mean Brier score 0. 43, 95% CI [0. 38 to 0. 49]) as compared with novices (mean = 0. 51, 95% CI [0. 48 to 0. 60] for a mean difference of 0. 08, 95% CI [−0. 18 to −0. 02]) and showed better specificity (0. 30 versus 0. 24). Experts were more pessimistic (i. e. , more likely to offer extremely low forecasts and less likely to use extremely high forecasts). We observed the opposite pattern for effect-size forecasts. scores (0. 17 versus 0. 25) and specificity (0. 68 versus 0. 59) for novices beat experts. We also explored the relationship between 4 expert/forecast characteristics and skill scores: confidence in their forecasts, expertise, age, and h-index (the former 3 were self-reported; see Fig 3). The most notable impacts on the forecasts were confidence (r = 0. 20, p < 0. 01) and h-index (r = −0. 15, p < 0. 01). High confidence was indicative of poor accuracy, since mean Brier scores increased (r = 0. 36, p < 0. 01 for significance forecasts) and specificity decreased as confidence increased for both outcomes. For effect sizes, low confidence was associated with greater fifty-fifty forecasting, whereas high confidence led to greater variability in the forecasts. Specificity and accuracy improved with h-index for both outcome types. For significance, higher h-indices were associated with pessimistic, and thus more accurate, forecasts (r = −0. 18, p < 0. 01). For effect sizes, a low h-index was associated with a high degree of fifty-fifty forecasting, and a high h-index was associated with lower forecasts (r = −0. 15, p < 0. 01). In fact, experts with a high h-index did better than “fence-sitting,” with a mean Brier score of 0. 17 and specificity of 0. 81. [SEP] Justify:

Output: The text is irrelevant to the claim as it discusses performance metrics concerning expert and novice forecasts without mentioning proteins or their functions. It focuses on accuracy and specificity in forecasting and does not provide any information related to protein properties or predictions.


Input: Task: corroborate the claim using the given text. Claim: Organic farming often relies on natural fertilizers like compost and manure rather than synthetic chemicals. [SEP] Text: The soil was air-dried, and plant material was sieved out of the soils and retained, coarsely chopped with a knife into 0. 01 to 0. 02-inch pieces and mixed back into the soil as uniformly as possible. Composted, pelletized poultry manure was used as a composted manure source for the study. A feather meal based amendment, Fertilizer 11-0-0 (advertised content 11N–0P–0K; Co. , Rowley, MA), and Fertilizer 5-5-5 (advertised content 5N–2. 2P–4. 2K, Co. ), were used as representatives of commercially available organic fertility management products. Ammonium nitrate was used as a conventional control. The CPM and amendment sources were analyzed, on a dry matter basis, for actual macronutrient content. CPM contained 4. 4% N, 1. 8% P, and 2. 5% K; Fertilizer 11-0-0 (hereafter referred to as 11-0-0) contained 10. 1% N, 0. 5% P, and 0. 6% K; Fertilizer 5-5-5 (hereafter referred to as 5-5-5) contained 6. 1% N, 1. 8% P, and 4. 8% K; ammonium nitrate contained 34% N. Treatments were designed to add CPM, 11-0-0, and 5-5-5 to the soils at a rate of 150 lb/acre, the recommended rate of N application for sweet corn in Wisconsin (Laboski et al. , 2006). The amount of CPM applied was determined using the N content from the laboratory analysis. Organic fertilizers were applied based on advertised N rates. We made this decision because growers typically have manure analyzed because of variability in macronutrient content. On the other hand, advertised macronutrient content of commercially available amendments is regulated and generally accepted by growers as accurate without further testing. The study was a completely randomized design with three replications of each soil/amendment combination. There were four cover crop treatments (alfalfa, pea, rye, and none) and five amendment treatments (11-0-0, 5-5-5, CPM, ammonium nitrate, and none), resulting in 20 treatments. [SEP] Justify:

Output: The text corroborates the claim by discussing the use of composted poultry manure as a natural fertilizer source in the study. It explains that organic fertilizers were employed based on their advertised nitrogen content and compares these organic options to a conventional control of ammonium nitrate. This demonstrates that the practices described align with the principles of organic farming—utilizing natural sources like compost instead of synthetic chemicals.


Input: Task: contrast the claim using the given text. Claim: AI can predict and prevent all health issues before they occur. [SEP] Text: Worryingly, extreme bushfire events of this scale are becoming more frequent, not just in Australia, but in many places around the world. This increase in the frequency and severity of bushfires is being driven by, among other things, human-induced climate change. Since the industrial revolution, humans have emitted more than two trillion tonnes of carbon dioxide and other greenhouse gases into the atmosphere. These gases trap heat from the sun in the Earth’s atmosphere, which has led to the destabilisation of climate systems all around the globe. In many places, dry seasons are becoming longer and hotter, which can create perfect conditions for bushfires to start. The risks associated with extreme bushfire events are being magnified as human populations continue to expand into forested areas. As human populations expand, we are seeing the associated expansion of the Wildland-(WUI). The WUI is defined as an area where people and houses are in close proximity to wildland vegetation. These areas are often characterised by very high fire risk due to the proximity of flammable vegetation and the difficulty of suppressing fires in these areas. As a result, understanding how bushfires behave and where they are likely to occur is more important than ever. and Marshall are researchers from the based at of Melbourne. Through their research, Kate, Erica and Trent investigate bushfires in an attempt to better predict patterns of bushfire behaviour and occurrence. This will allow them to identify where future fire risks are highest, and help communities prepare for and manage the risks associated with bushfires. What are the risks posed by bushfires? “Bushfires can cause extensive impacts on the environment and people,” says Trent. “The most serious direct impacts include the immediate loss of life and property during extreme events. ” Bushfires can also result in the widespread destruction of habitat and increase the risk to threatened plant and animal communities. The impacts from extreme bushfire events can linger for a long time after the fires have been extinguished. This is particularly true for economic impacts, such as the loss of tourism, the destruction of farm crops and damage to local shops and businesses. Long-lasting economic impacts can put huge pressure on local communities. As families are displaced and community groups broken up, the mental health and well-being of people can come under serious strain. The risks posed by bushfires may vary in different areas. [SEP] Justify:

Output: The text contrasts the claim by discussing the challenges posed by extreme bushfire events and how human-induced climate change exacerbates these issues. It focuses on predicting and managing bushfire risks rather than health issues, indicating that there are limitations to what can be predicted and prevented, including environmental disasters like bushfires. Furthermore, the impact on people's mental health and community well-being emphasizes that not all risks—especially those associated with natural disasters—can be completely prevented or predicted by AI.


Input: Task: pass the claim using the given text. Claim: Certain researchers argue that the properties of proteins can predict their functions accurately. [SEP] Text: When comparing expertise measures, experts were more accurate when they had general, compared to identified, expertise across h-index levels. The third of experts with the lowest h-indices were more discrepant, as Brier scores decreased by 0. 09 on average when they had identified expertise, whereas the decrease was only 0. 03 for the other two-thirds of experts. Download: PPTPowerPoint slidePNGlarger imageTIFForiginal imageFig 3. Forecasts and Brier scores by discretized predictors. All graphs show violin plots with embedded box plots and medians. and B display forecasts and Brier scores, respectively. Top and bottom rows show results for significance and effect-size forecasting, respectively. The columns show 4 predictors: self-reported confidence, self-reported expertise, age, and h-index (i. e. , mean indices obtained from Scopus and Web of Science). Predictors were trichotomized to give approximately equal group sizes. we explored whether gender showed a relationship with forecasts and accuracy. Female experts gave forecasts that were about 8% higher on average than their male counterparts for both significance and effect size; female novices’ forecasts were about 6% higher on average than males for both. As a result, females’ Brier scores were higher than males’ both on replicability of significance (mean Brier score = 0. 48, 95% CI (0. 42 to 0. 66) versus mean Brier score = 0. 42, 95% CI [0. 35 to 0. 47]) and effect size (mean Brier score = 0. 32, 95% CI [0. 21 to 0. 46] versus mean Brier score = 0. 25, 95% CI [0. 20 to 0. 30]). Novice females also were less accurate than their male counterparts on significance replicability (mean Brier score = 0. 56, 95% CI [0. 50 to 0. 67] versus mean Brier score = 0. 46, 95% CI [0. 41 to 0. 66]) and effect size (mean Brier score = 0. 28, 95% CI [0. 21 to 0. 39]) versus mean Brier score = 0. 22, 95% CI [0. 16 to 0. 34]). The gender difference for replicability of effect-size forecasts was significant for both experts (0. [SEP] Justify:

Output: The text is irrelevant to the claim as it discusses various aspects of expertise and forecasting accuracy without addressing the predictive properties of proteins and their functions. It focuses on comparisons of expert accuracy and gender differences in forecasting rather than on protein functions.


Input: Task: corroborate the claim using the given text. Claim: Organic farming often relies on natural fertilizers like compost and manure rather than synthetic chemicals. [SEP] Text: , 2017; Olufolaji et al. , 1990). Crop residues return small amounts of organic materials to the soil as a way of nutrient recycling. Agricultural waste and food/industrial by-products are organic materials that could be good sources of organic soil amendments needed to maintain soil fertility at levels that can support the growth of amaranth. Manures serve as organic fertilizers in many agronomic production systems. They add soil organic matter (SOM) and decompose it into stable humic substances (Davison et al. , 2000), while supplying macro- and micronutrients (Usman, 2015). As a reservoir of plant nutrients, SOM needs to be manipulated to promote soil fertility and ensure success in humid tropical agriculture (Obalum et al. , 2011). Accretion of SOM promotes soil aggregation and structure of coarse-textured soils to enhance water retention, thereby slowing down nutrient mineralization, and favouring sustenance of beneficial soil organisms (Obalum et al. , 2017). Conventional animal manures are often used as organic soil amendments in amaranth production (Ainika, 2010; Bawa, 2010). However, poultry droppings (PD) can be scarce, and this is aggravated by its other important uses, including serving as a substrate in the bioremediation of crude-oil polluted soils (Ezenne et al. , 2014). [SEP] Justify:

Output: The text corroborates the claim by explaining how manures are utilized as organic fertilizers in agronomic production systems, specifically highlighting their role in adding soil organic matter and supplying essential nutrients. It emphasizes the concept of using organic materials, such as manures and agricultural waste, for nutrient recycling in soil, aligning with the principles of organic farming.


Input: Task: contrast the claim using the given text. Claim: AI can predict and prevent all health issues before they occur. [SEP] Text: As a result, they have an intimate understanding of their native lands and how best to manage them. What range of expertise is there in FLARE? is one of Australia’s largest fire research groups. “In our group, we have an incredibly broad range of skills and backgrounds including landscape and animal ecology, combustion engineering, forest science, mathematical modelling, and some data analysis and computer programming thrown in for good measure,” explains Erica. Every researcher at FLARE has followed a unique path to their current work. This diversity of research experience enables them to investigate and answer some of the complex questions that face fire management agencies all over the world. “Having this fantastic diversity of backgrounds and skill sets allows us to do innovative, unique and rigorous research on a range of wildfire related subjects,” says Trent. What is a typical day like for FLARE researcher? Most of the day-to-day activities focus on conducting research, either through experiments, field-work or simulation modelling. The team also spends a lot of time writing up research papers, communicating with industry partners and carrying out statistical modelling. Erica explains, “On an average day, we might be writing new code for our models, analysing field and experimental data, or engaging with collaborators about common research projects. ” Documenting the group’s work in the form of reports, peer-reviewed publications and presentations is also vital. “This process is critical for getting our research into the scientific community and advancing the collective knowledge on wildfire risk,” says Kate. What is rewarding about being a bushfire researcher? The work of bushfire researchers can have significant impacts on how land managers understand and manage fire. “Knowing that the work we do is respected and applied by local and state governments, as well as our private industry partners, is very rewarding,” says Trent. “Every improvement to our understanding of bushfire risks can improve our management of those risks and potentially prevent impacts on the environment and our communities. ” Pathway from school to bushfire risk analysis • At school and post-16, take maths alongside other science subjects like biology and chemistry. • Learn about the practical skills that you might need for field data collection. “For me, this is the best part,” says Kate. “I love getting out in the field and collecting information on species, ecosystems or processes. [SEP] Justify:

Output: The text contrasts the claim by discussing the work of bushfire researchers at FLARE who focus on understanding and managing risks related to bushfires rather than health issues. The mention of diverse expertise in areas like ecological and combustion engineering shows that while they conduct valuable research applicable to risk management, it does not support the notion that AI can predict or prevent health issues. Additionally, the emphasis on the importance of their research for local and state governments indicates a focus on environmental rather than health-related concerns.


Input: Task: pass the claim using the given text. Claim: Certain researchers argue that the properties of proteins can predict their functions accurately. [SEP] Text: 07, 95% CI [−0. 24 to −0. 02]) and novices (0. 06, 95% CI [−0. 18 to −0. 07]). Sensitivity analysis The results from Study 29 have not yet been revealed. We performed a sensitivity analysis to determine how the results would change contingent on the eventual results of that study. The sensitivity results are shown in Figs 2 and 3 and S5 Table in the Supporting Information. Significance forecasts for Study 29 were less optimistic (median of 75%), and effect size forecasts were more pessimistic (median of 40%) than all but 1 of the other studies. Overall, Brier scores will improve regardless of whether Study 29 reproduces the original effect. However, potential gains would be modest and would still underperform a fence-sitting strategy (Brier score = 0. 25): If RP:CB results replicate Study 29, the overall mean Brier score would improve from 0. 41 to 0. 38, whereas if RP:CB does not replicate Study 29, it would be 0. 40. If RP:CB replicates the results of Study 29, the mean Brier score for significance forecasts would improve significantly from a mean of 0. 57 to 0. 48 (95% CI [0. 45 to 0. 51]) and would show less improvement if Study 29 does not replicate, to 0. 54 (95% CI [0. 50 to 0. 58]). The change for effect size forecasts would be smaller, but a positive replication would make the mean Brier score worse, from 0. 26 to 0. 29 (95% CI [0. 26 to 0. 32]), and a nonreplication would improve it to as good as a fence-sitting strategy (0. 25, 95% CI [0. 18 to 0. 25]). All of the changes would be significantly different from the current results. DiscussionOur findings suggest that, on average, preclinical cancer researchers are overly optimistic in their beliefs about reproducibility. Half of all expert forecasts indicated that the replications were more likely to replicate original results than not, whereas only one-third indicated greater likelihood of replication failure. Overconfidence in reproducibility of specific results was particularly prevalent in significance forecasts, where 73% of expert forecasts favored successful replications. Forecasters were less certain (and more pessimistic) about replicating effect sizes. There are several ways of interpreting our findings. [SEP] Justify:

Output: The text does not address the claim regarding the relationship between the properties of proteins and their functions. Instead, it discusses the findings of a study related to reproducibility and forecasts in research, which is unrelated to the claim about protein functions.


Input: Task: corroborate the claim using the given text. Claim: Organic farming often relies on natural fertilizers like compost and manure rather than synthetic chemicals. [SEP] Text: Cattle dung (CD) that is not scarce has a high carbon-nitrogen (CN) ratio and mineralises less readily in the soil (Chukwuma et al. , 2024; Ndzeshala et al. , 2023; Uzoh et al. , 2015). Composting of organic materials before soil application ensures the stability of SOM and the release of nutrients to the soil (Baiyeri et al. , 2020; Tiquia, 2003). Amaranth growth can be increased with soil application of composted plant residue and a mix of animal waste (Dada et al. , 2017). One potential constraint, however, is the short-lived nature of the compost effect on soil structure stability (Obalum et al. , 2019). These prospects and constraints of composts and of PD and CD manures (in terms of availability and mineralization rates) offer an opportunity to explore the prospects of mixing plant waste with animal manures before composting, thereby developing sustainable enhanced productivity of amaranth and similar leafy vegetables all-year-round. Any lack of residual effects of conventional compost on soil structure stability (Obalum et al. , 2019) and yield of vegetable crops may be compensated for by PD and CD manures (Ogunezi et al. [SEP] Justify:

Output: The text corroborates the claim by discussing the use of cattle dung (CD) and composting of organic materials as part of organic farming practices. It emphasizes that composting enhances soil nutrient availability and stability of soil organic matter (SOM), aligning with the claim that organic farming employs natural fertilizers such as compost and manure.


Input: Task: pass the claim using the given text. Claim: AI can predict and prevent all health issues before they occur. [SEP] Text: • Centre for Wildfires, Ecology and Society website is a great resource to learnmore about bushfires and how they affect ecosystems and communities. Its website has sections for new research being published, the latest news in wildfire research and jobs. It also hosts events and talks where you can learn more about the field of bushfire research. • Get in touch with your local university or college to see if it has a department that studies bushfire management and offers any volunteering or research opportunities. Gaining experience of working as a researcher of any kind can provide you with valuable experience and help you explore your career options. What were your interests when you were growing up? As a kid, I always had my pockets full of something. I couldn’t help myself – I was constantly picking things up to take home and investigate later. I collected rocks, plants, sand, sticks and shells… I was always rescuing injured birds, insects, lizards and worms. I just really loved being out in nature. I had a strong environmental focus from an early age. was about 12, I joined a local ‘Stream Watch’ club that assessed water quality and surveyed the local aquatic wildlife once a month. This taught me a lot about how to run scientific experiments, and I was hooked. However, I also really loved acting and singing, so I was often torn between science and the arts. The best part of my current role is that I can combine my love of science with my love of communicating to explain science in fun and exciting ways. Who inspired you to become a scientist? David Attenborough’s documentaries were mind-blowing to me as a kid. I would watch these films and make a ‘bucket list’ of species I wanted to see and places I wanted to go one day. I was also extremely lucky to have family friends who were working zoologists, so I spent many holidays with them wading through lakes, chasing frogs or spotlighting (a way of observing nocturnal animals in the dark). I knew from an early age that I wanted a job that felt meaningful, and that allowed me to be out in nature. What attributes have made you successful as a scientist? I think one of the key things that makes me a successful scientist is that I have a deep curiosity about the world around me and a drive to do research that will have direct and tangible impacts. I like tricky and complicated questions, and I am motivated to find the answers. [SEP] Justify:

Output: The text is irrelevant to the claim as it discusses personal experiences and insights related to environmental science, wildlife research, and the journey of becoming a scientist. It does not address AI, health issues, or predictive technologies in any way, therefore it does not corroborate or contrast the claim.


Input: Task: pass the claim using the given text. Claim: Certain researchers argue that the properties of proteins can predict their functions accurately. [SEP] Text: A different version of this interpretation is that some participants responded to our forecast questions with their beliefs about the underlying biological claims, rather than instantiations of them in particular laboratory experiments. In response, we point out that 2 of the 5 studies in our survey (19 and 21) were widely reported as having confirmed underlying biological claims, while 1 of the studies (15) was reported as having been disconfirmed [25]. If forecasts were right in the generalities, we would expect forecasts to be consistently higher for 19 and 21 than for 15 for both measures of replication. 1 shows, forecasts were pessimistic for Study 21 and relatively moderate for Study 15. Although our study was not designed to discriminate between these various interpretations, it raises important questions about the way expert researchers interpret the sorts of high-impact findings tested in RP:CB. We find that biomedical scientists are inclined to overestimate the validity of original reports and/or underestimate the difficulty in conducting direct replications. The latter would perhaps be of less concern for science policy than the former. However, inability to appreciate the sensitivity of original reports to subtle laboratory conditions or aleatory uncertainty can result in potentially unfruitful debates about reproducibility, as well as wasted efforts as laboratories vainly attempt to follow protocols in original reports. It is beyond the scope of this paper to discuss the quality and reliability of experiments employed by the RP:CB. Scientific reports and news coverage of RP:CB have highlighted the difficulties in implementing replication studies (e. g. , the commentaries reacting to the RP:CB results in eLife, Nature, and Science). We make no claim here about whether or not the RP:CB studies we examined constitute a gold standard of replication. We merely note that the manner in which such questions are resolved has implications for the interpretation of our results. Nevertheless, if—as many critics suggest—RP:CB experiments inadequately implemented original methods, our findings do not suggest these failings were apparent to our participants. If forecasting improved with expertise, then some risks of overconfidence might be mitigated. Elsewhere, experts have been found to be as overconfident as novices, and the relationship between expertise and predictive skill is complex and task dependent [27,28]. In our study, greater topic expertise did not improve forecasting: indeed, experts displayed greater overconfidence when they were more familiar with a study and in general did not outperform our sample of trainees. [SEP] Justify:

Output: The text does not address the claim regarding the predictive properties of proteins and their functions. Instead, it discusses issues related to the interpretation of biological claims, the validity of original reports, and the difficulties of conducting replication studies. Therefore, it is irrelevant to the claim.


Input: Task: corroborate the claim using the given text. Claim: Organic farming often relies on natural fertilizers like compost and manure rather than synthetic chemicals. [SEP] Text: , 2019; Onah et al. , 2023; Sanya & Amadji, 2018). Brewery waste (spent grain) is an industrial by product that is generated in large quantities and poorly disposed (Devolli et al. , 2018; Nassary & Nasolwa, 2019; Onwe, 2004). One way of recycling brewery spent grain (BSG) could be by composting it into organic fertilizers, as composted BSG has a high potential for releasing essential nutrients for plant growth (Ebido & Ndubuaku, 2019; Kanagachandran & Jayaratne, 2006). Owing to the prevailing abundant discharge of its source and its ability to enhance soil fertility, composted BSG may appeal to subsistence vegetable farmers, and may be deemed a promising suitable and economically viable option for them. Little is currently known of the efficacy of complementing composts with animal manures of varying CN ratios, or the suitable combining ratio, in organic amaranth farming. This study was undertaken to determine the agronomic effects of a composted mix of BSG with PD or CD on amaranth growth and yield in acid sandy tropical soils. 2. Materials and Methods2. [SEP] Justify:

Output: The text corroborates the claim by discussing the recycling of brewery spent grain (BSG) into organic fertilizers through composting, which aligns with the idea that organic farming utilizes natural fertilizers. It states that composted BSG has a high potential for releasing essential nutrients for plant growth, reinforcing the reliance on natural methods in organic farming.


Input: Task: contrast the claim using the given text. Claim: AI can predict and prevent all health issues before they occur. [SEP] Text: Themes and thrusts of our reviewWe devote special attention to three recent important publications offering predictive models of genocide and mass atrocities: Verdeja (2016), Maynard and Benesch (2016), and the UN Framework of Analysis for (2014) [29,30,31]. These reviews consider legal and historical aspects of genocide and mass atrocities and offer predictive models from case studies. Verdeja reviews a number of predictive models for genocide and mass atrocities and distinguishes between risk assessment (RA) and early warning (EW) models. Risk assessment is based on long-term structural variables of a country or area. Early warning examines factors that can trigger immediate acts of violence. Maynard and Benesch develop a model integrating “dangerous speech” (incitement) and the ideologies behind them. The UN Framework lists a number of risk factors with subsequent indicators that can be used to predict future mass atrocities. What is noteworthy is that these papers pay little attention to the upstream role of indoctrination leading to the perpetration of violence. Verdeja includes “hate media,” “public rallies,” and “popular mobilization” among the early warning indicators of genocide prediction models [29]. Maynard and Benesch note the “ideological context” behind violent acts. Indoctrination is the missing piece connecting the two. The UN statement includes supremacist ideologies, inflammatory rhetoric, and hate speech as indicators. However, not once is the term “indoctrination” used. This is particularly telling, as incitement alone is not enough to predict violence. In his empirical study to test the causal effects of radio incitement on acts of violence in Rwanda, Straus was unable to prove a direct relationship between incitement and violence [32]. His analysis demonstrates that incitement alone is not the primary cause of killing, mass murder, beheadings, rape, torture, forced expulsion, and other crimes against humanity. Rather, he says, incitement is effective only in the event of preconditions. We propose that these preconditions are systems of indoctrination. This statement seems intuitive. Simply hearing hate speech on the radio will not automatically send every individual off to begin killing. Only those who have been sensitized to such messages over time will actually act upon them. Thus, a predictive model must include such upstream factors. Recent literature on terrorism lacks sufficient discussion of the critical role of indoctrination. [SEP] Justify:

Output: The text contrasts the claim by discussing predictive models related to genocide and mass atrocities, indicating that predictive models need to include upstream factors like indoctrination. It highlights that incitement alone does not lead to violent actions without underlying preconditions, suggesting that prediction models are complex and cannot ensure prevention without a comprehensive understanding of contributing factors.


Input: Task: pass the claim using the given text. Claim: Certain researchers argue that the properties of proteins can predict their functions accurately. [SEP] Text: This might be explained by experts having a tendency to take the “inside view”—a focus on the unique details of each specific experiment—over the “outside view”—a focus on the class of similar events [29]. The outside view tends to beat the inside view in predictive judgments [30]. On the other hand, our observations hint at the prospect that greater researcher impact (as measured by h-index) was associated with more accurate forecasts. Some reasons to expect experts to outperform nonexperts are they search for fewer total but more diagnostic cues and rely more on their existing knowledge and strategies [31]. We urge caution interpreting our results since reproducibility is difficult to define and measure [32]. Our survey scored forecasts using common forecasting methods that dichotomize whether studies reproduce based on 2 different criteria (significance and effect size). A strength of this method is that it creates predictive judgments that are verifiable. Participants’ judgments do not represent participants’ comprehensive beliefs about the treatment mechanisms at hand. However, it is rarely possible to capture such judgments in a manner that can be verified in a timely fashion. We do not suggest the forecasts collected in our study reflect judgments concerning fundamental scientific relationships generalized beyond the context in which they are tested. Additionally, replication is not an “all or nothing” phenomenon; 2 replication studies failed to reproduce statistical significance and had greatly diminished effect sizes but nevertheless showed effects that—when meta-analyzed with the original report—excluded the null hypothesis. Therefore, interpreting the overall success of these replications is to some degree in the eye of beholder. Moreover, a failed replication is not the same as evidence that the effect does not exist. However, there is no prescribed degree of disparity from an original result that is considered tolerable [33]. If the original and replication studies were sound methodologically, it can be difficult to judge if the original study overestimated or if the replication underestimated a true effect [34]. Our findings are subject to several limitations. First, despite a vigorous recruitment effort, our response rate was probably low, and our bounce rate was high. This may reflect some controversy surrounding the RP:CB. Nevertheless, we were able to capture a meaningful sample of experts: 138; this figure compares favorably with other studies requiring esoteric, expert research participants. [SEP] Justify:

Output: The text does not address the claim about the predictive power of protein properties regarding their functions. Instead, it discusses the challenges and complexities involved in making accurate forecasts and judgments in research, particularly in the context of expert opinion and replication studies. It does not provide any direct support or contradiction to the claim about protein function prediction.


Input: Task: corroborate the claim using the given text. Claim: Organic farming often relies on natural fertilizers like compost and manure rather than synthetic chemicals. [SEP] Text: 1 Characteristics of the Experimental SiteThe experiment was conducted at the Garden, Teaching & Research Farm, University of Ibadan, Ibadan, Nigeria (7° 24’N, 3° 54’E; 62 m asl). The farm is located in the derived savannah of southwestern Nigeria. The mean monthly temperature ranges from 24 to 30℃ and the mean annual rainfall from 1,800 to 2,100 mm. The field study was conducted on an acid sandy soil. Some physicochemical properties and fertility indices of the top 0-20 cm soil before the study were assayed following standard laboratory procedures (Sparks, 1996). 2. 2 Treatments, Field experiments were carried out to determine effects of BSG-based compost on the growth and the yield of green amaranth as organic soil amendments. The BSG was composted with and without PD and CD, involving soil application of composted BSG and a composted mix of BSG with PD or CD. The PD and CD were chosen as manures because of their known wide difference in CN ratio, with smaller values in the former than the latter (Adubasim et al. , 2018), which translate into their faster and slower mineralisation, respectively in coarse-textured tropical soils (Chukwuma et al. , 2024). The BSG was supplied by the the PD and CD were obtained from the Teaching & of the Department of Animal Science, Faculty of Agriculture and Fisheries, University of Ibadan, Ibadan, Nigeria. The composting of BSG and its mix with PD or CD was done under controlled well-aerated environmental conditions in the Garden of the Teaching & Research Farm. In initiating the composting, these three organic wastes were used in their fresh forms as procured and were not subjected to curing by sun-drying. Each of BSG+PD and BSG+CD was composted in volume ratios of 1:1 and 2:1, each having two replications. [SEP] Justify:

Output: The text corroborates the claim by detailing an experiment that involves the use of organic soil amendments, specifically mentioning the use of composted BSG (Brewer's Spent Grain) along with organic manures PD (Poultry Droppings) and CD (Cow Dung). This demonstrates reliance on natural fertilizers, supporting the notion that organic farming utilizes such natural inputs instead of synthetic chemicals.


Input: Task: contrast the claim using the given text. Claim: AI can predict and prevent all health issues before they occur. [SEP] Text: Such models need not be limited to the study of disease. Social behavior can mimic the spread of biological organisms (think of a “viral” video spreading across social media) [15]. Social scientists can take social phenomena and apply epidemiologic models to track and measure their spread. We propose taking models used to track the health effects of air pollution to track and measure the effects of word pollution. Such pollution consists of incitement and, more importantly, the role of indoctrination in producing such incitement. The messages and motifs of word pollution are without borders, embedded in cyberspace, with universal reach. Therefore, there is a need to gather empirical data concerning factors that contribute to individual and population resistance to these motifs and messages and to propose strategies that counter the negative effects of such ideologies. By defining hateful motifs and messages as an exposure, we can track and explore exposure-effect relationships, track source, intensity, and frequency, and monitor time frames. We can also examine the social circumstances that influence the effects of varying motifs and messages, which can provide insight into which interventions might be effective in preventing the spread of hateful indoctrination and incitement. Stein and Richter propose several relevant epidemiologic models and appendices in their 2012 monograph and present empirical data and ecologic correlations which state the case for prediction, precaution, and prevention [15]. While other epidemiologic models such as social determinants, ecologic, and complex systems models might offer explanations and insights for preventive efforts, we focus on the infectious disease model based on the premise that word pollution most closely resembles the spread and effect of community-wide air pollution–as has been extensively studied in Beijing and [37, 38]. modelThe “Iceberg model” of disease shows how, for every hospitalized patient suffering severe disease symptoms, thousands more “walking sick” exist with subclinical disease who should be targeted for intervention and many more are at risk due to background effects or exposures [39]. Applied to terror, the Iceberg model expresses the concept that perpetrators are drawn from a larger population-wide pool of increasing degrees of risk and participation as sympathizers, endorsers, followers, recruits, and ultimately participants or perpetrators (see Fig. 1, Iceberg model of disease applied to terror). For example, supporters of an ideology that glorifies acts of genocide or genocidal terror may themselves be passive. [SEP] Justify:

Output: The text contrasts the claim by discussing the limitations of predictive modeling, focusing on social behavior and its effects rather than directly supporting the idea that AI can predict all health issues. While it introduces the idea of epidemiologic models for tracking health effects, it highlights the complexity and difficulty in prediction, such as the need to gather empirical data to counter harmful ideologies, which illustrates that not all health issues can be predicted or prevented.


Input: Task: pass the claim using the given text. Claim: Certain researchers argue that the properties of proteins can predict their functions accurately. [SEP] Text: The mean h-index for responders was somewhat lower than for nonresponders, suggesting our participants may have been slightly younger or marginally less productive than our sample population. However, the upper third of our sample had a high h-index (49. 1 on average compared to 32. 4 for the average nonresponder), including 22 experts with h-indices exceeding 40. Second, the gender imbalance in our expert sample is notably larger than in our novice sample. This imbalance may reflect an inherent gender imbalance between senior and junior researchers. Experts in life sciences tend to be primarily male (for example, 25% of tenured faculty positions in the biological and life sciences were held by females in 2013 [35]), while trainees tend be more female (for example, 53% of biological doctorates were awarded to women that year [36]). Females’ forecasts were about 6% higher on average, but the overall patterns of optimism held across gender. Third, our sample of experiments was small, and there was no variability in the reported results. We selected xenograft experiments because they are generally regarded as more predictive of clinical utility and the results were verifiable; this choice limited the number of available studies. We selected experiments a priori without any knowledge of outcomes, and the lack of variability in outcomes ultimately limited our ability to test researchers’ capacity to discriminate between studies that reproduce from those that do not. Our findings should therefore be replicated in a larger sample of experiments before drawing conclusions about the forecasting skill of cancer biology experts. Fourth, we do not know what the forecasters were intending to communicate when they offered forecasts. Forecast methods do not account for forecaster motivation. Indeed, the use of a “proper scoring rule” is intended to incentivize truthful—as opposed to strategic or motivated—disclosure of belief. Nevertheless, forecasters could have intended optimistic forecasts as a way of portraying the field positively or defending it against skepticism. Paradoxically, participants may have intended to express relative pessimism about reproducibility, since forecasts tended to be lower than participants’ expectations about perfectly reproducible effects (see S3 Fig in the Supporting Information). Such pessimistic forecasts could be a hedge so that the cancer field in general would appear better than predicted if replication results were “positive. ” In any event, unconscious motives often play a role in survey responses and cannot be excluded as an explanation for the observed patterns. [SEP] Justify:

Output: The text does not address the claim regarding researchers arguing that the properties of proteins can predict their functions accurately. Instead, it discusses factors like h-index, gender imbalance among researchers, and the challenges in reproducibility in cancer biology without mentioning anything specific about protein properties or their functions.


Input: Task: corroborate the claim using the given text. Claim: Organic farming often relies on natural fertilizers like compost and manure rather than synthetic chemicals. [SEP] Text: The composted organics were designated BSG+PD(1:1), BSG+PD(2:1), BSG+CD(1:1), and BSG+CD(2:1). The composting period was six weeks with temperature readings taken daily using a compost thermometer. To ensure aeration within the compost pile, the mass was turned at the beginning of the second, fourth and fifth weeks when the pH of the compost was determined and the pile moistened. The temperature of the compost reflecting the activity of micro-organisms and the pH of the compost together were used to infer its maturity. After the composting period, composts were spread and left for curing (air-drying to reduce pathogenic load) for four weeks before use. The field experiment, described by Ebido & Ndubuaku (2019), involved composted BSG+PD(1:1), BSG+PD(2:1), BSG+CD(1:1), BSG+CD(2:1), BSG as a reference, and an unamended control as a treatment. The experimental arrangement was a randomized complete block design with four replicates. Plots measuring 1. 5 × 1. 0 m were guarded against external interferences with earthen bunds (compactly prepared ridges) and were 0. 50 m apart. Manual hoeing to about 20-cm depth was done in all plots. Thereafter, composted organic amendments were uniformly spread on the surface of the plots at the rate of 20 t ha–1. A pack of amaranth seeds, of cv. PI 511679, was purchased from Eagle Seeds, Orogun Ibadan, Nigeria. This genotype, grown mainly for its leaves, usually grows up to 25 cm tall with about 11 leaves in about four weeks on un-amended soils in the study environment (Adeoluwa et al. , 2009). Three days after hoeing the soil and spreading the composted organic amendments, seeds were sown in drills spaced 0. 50 m apart. [SEP] Justify:

Output: The text corroborates the claim by describing the use of composted organic amendments in farming practices. Specifically, it details the composting process and application of composted materials, which aligns with the assertion that organic farming utilizes natural fertilizers instead of synthetic chemicals.


Input: Task: contrast the claim using the given text. Claim: AI can predict and prevent all health issues before they occur. [SEP] Text: However, with repeated stimuli, these supporters can become active participants. Fig. 1Iceberg model of disease applied to terrorFull size imagePerpetrators are at the top of the epidemiologic iceberg, either as members of groups or as individuals. These perpetrators come from a larger pool of already sensitized individuals and groups and can be activated by triggers towards the pinnacle of a multistage process. The model is dynamic. Individuals and groups move up and down in relation to exposure to incitement and susceptibility to its effects. At any given moment, there are segments of the population at each of the levels. With enough exposure to the aggravating agents (in the case of word pollution—indoctrination), members of a lower rung in the pyramid can rise up to higher levels. Intervention or deterrence directed at removing or neutralizing the actions of those at the top of the iceberg by itself cannot be expected to remove the source of the influence directed at the entire population. It is futile to simply hunt for terrorists when radical ideologies prevail in entire populations. The best example is that the assassination of did not kill off Al-Qaeda. Prevention or eradication of genocidal terror requires more than tactical defeats or punitive measures against the perpetrators of violence. Population-wide counter-strategies must be implemented. modelA second model is the model [40]. Rose, an epidemiologist, coined the concepts “sick populations and sick individuals” and “the mean determines the range” [41]. These concepts indicate how population-wide interventions to remove hazardous exposures are more effective at reducing the total number of diseased individuals than interventions treating a smaller number of sick individuals at the peak of the iceberg. The implication is that population-wide measures can shift the entire range of the population distribution towards greater health. For example, reducing the population-wide exposure to salt in our diets is a population base approach to augment case finding and treatment of individuals with high blood pressure. We can apply the Rose model to indoctrination. Population-wide exposure to indoctrination that leads to incitement, genocide, and genocidal terror pushes the mean towards the “sick group”—the perpetrators of violence (metaphorically “heating-up heads”) [6]. The implication is that population-wide countermeasures that target susceptible groups, those at high risk from exposure, will be more effective than targeting sick individuals. [SEP] Justify:

Output: The text contrasts the claim by illustrating that intervention strategies must target broader population-wide issues rather than relying on the prediction or prevention of individual health problems. It emphasizes that effective health interventions require a comprehensive approach, such as reducing population-wide exposure to hazardous factors, which contradicts the notion that AI can predict and prevent all health issues on an individual basis.


Input: Task: pass the claim using the given text. Claim: Certain researchers argue that the properties of proteins can predict their functions accurately. [SEP] Text: Fifth, our surveys assumed a certain amount of statistical knowledge. For example, asking individuals whether replication studies would achieve statistical significance (p ≤ 0. 05) requires understanding what a p-value measures. We regard this as a potential strength, however. Scientific reports routinely convey claims through metrics like p-values or standardized mean differences. Therefore, the ability to derive valid inferences from such metrics is integral to forming judgments about effects and reproducibility. Expert predictive judgment in biomedical research has not, to our knowledge, been previously studied. Scientists tend to focus on finding physical truths, and discrepancies between results often trigger debate about the methods used in each study. We suggest the role of scientific judgment is also important because physical truths can never be proven with certainty. The judgment of experts thus determines—at least in the short term—the way discrepant results are interpreted and which findings are taken as fact. Our study provides evidence that community-wide judgments about reproducibility are overoptimistic and overconfident. The assessment and cultivation of researcher judgments, we suggest, may lead to a more efficient research enterprise. Knowing how well biomedical researchers can predict experimental outcomes is crucial for maintaining research systems that set appropriate research priorities, that self-correct, and that incorporate valid evidence into policy making. Regardless of how one interprets our results, these findings have potential policy implications, since they suggest that biomedical scientists have a difficult time anticipating outcomes when high-impact experiments are repeated. We believe it would be valuable to work to improve the judgments of researchers and trainees. There are common traits of domains in which experts’ forecasts tend to be more accurate and discriminating. Judgments must be formally quantified, and feedback should be timely, as unambiguous as possible, and easily compared to the original forecast [37]. Forecasting skill may also be better in domains in which expert judges are directly accountable to skeptical constituencies for the quality of their predictions [38]. We cannot expect researcher judgments to improve until the proper structure is in place to help them succeed. statement Human participant procedures were approved by the McFaculty of (Protocol #A01-B05-16A). Each participant provided informed consent before commencing. recruited experts using a 2-pronged search for authors of publications related to the first 6 studies in RP:CP (a flow chart of the sampling process is shown in S1 Fig in the Supporting Information). [SEP] Justify:

Output: The text is irrelevant to the claim as it discusses issues related to the understanding of statistical significance and expert predictive judgment in biomedical research, without addressing the relationship between protein properties and their functions. The claim specifies a connection between protein characteristics and functional predictions, which is not mentioned or supported in the text.


Input: Task: corroborate the claim using the given text. Claim: Organic farming often relies on natural fertilizers like compost and manure rather than synthetic chemicals. [SEP] Text: The soil had a slightly acidic pH and a high level of exchangeable acidity. The available phosphorus (P) level was slightly high; the exchangeable potassium (K) and sodium (Na) indicated very low to low values according to the rating of Landon (1991). Table 1. Selected chemical properties of the soil before treatment applicationSoil PropertiesValueTexture classLoamy sandSoil pH-H2O5. 3Soil organic carbon (g kg-1)19. 20(g kg-1)2. 31(mg kg-1)23. 00Exchangeable bases and acidity (cmol kg-1)K+0. 10Ca2+1. 80Mg2+0. 40Na+0. 10H+0. 40Al3+0. 503. 2 on Parameters of AmaranthThe immediate effects of the composted BSG-based organic soil amendments showed that the treatment affected amaranth growth (Table 2). Treatment generally increased plant height, stem diameter and the number of leaves of amaranth plants compared with the un-amended control. Composted BSG+PD(1:1) produced taller plants and more leaves compared with the control; composted BSG+CD(2:1) gave the widest stem of the amaranth plants and the control the narrowest. For this stem diameter, composted BSG+PD(1:1) and BSG+PD(2:1) showed similar values. In addition, composted BSG+CD(1:1) and BSG+CD(2:1) had similar stem diameters, with the former being similar to the rest of the treatments excluding the control. Composted BSG+PD(1:1) and BSG+CD(1:1) were similar in all three growth indices; so too were composted BSG+PD(2:1), composted BSG (the reference) and the control, and composted BSG+CD(1:1), composted BSG+CD(2:1) and composted BSG. Table 2. [SEP] Justify:

Output: The text corroborates the claim by discussing the use of composted BSG (Brewer's spent grains), which is a type of organic soil amendment, in enhancing the growth parameters of amaranth plants. This indicates that organic farming practices, such as applying compost, are employed instead of synthetic chemicals, aligning with the claim that organic farming often uses natural fertilizers.


Input: Task: contrast the claim using the given text. Claim: AI can predict and prevent all health issues before they occur. [SEP] Text: We are not aware of this concept having been applied to the epidemiology of genocidal indoctrination and incitement unto terror as of yet. We recognize that there may be times that the range determines the mean. High-risk individuals may themselves have an influence on the rest of the population by serving as heroic role models or passing on incitement to others. The people at the tails can pull the entire population to opposing directions. This concept is relevant to both negative and positive deviance and their impact on behavior. By reducing population-wide exposure to hateful indoctrination and introducing measures that strengthen positive deviance, the mean and distribution of susceptible groups can be shifted away from the so-called sick group towards greater health. Positive deviancePositive deviance refers to the observation that, in every population group, there are individuals at the positive end of the spectrum. These outliers are worthy of emulation and should be strengthened. For example, in any cases of mass violence, there are always individuals who defiantly refuse to “join the crowd” [42]. They resist both official orders and social trends. The basic concepts of positive deviance come from the classic works of Milgram. He found that there are always individuals who disobey orders or social pressures that contradict their personal judgment or values. In his study on obedience, Milgram addressed the participants who refused instructions in the simulated shock experiment [43]. In public health, these are the individuals who resist social pressure to smoke cigarettes, use drugs, or engage in other high-risk or socially harmful behaviors. Shamir explored this concept of positive deviance in his documentary “10%, a Hero? ” [44]. He studied people who resist societal trends in accordance with their personal convictions. The challenge for those concerned with genocide and genocidal terror is to identify individuals that are resistant to the effects of exposure to hate indoctrination and incitement and to have their examples serve as multipliers. The fact that such individuals exist in every social group offers the potential for prevention. Examples of positive deviance are the from the Holocaust, and the Movement, the in the UK, Dr. Qanta A. Ahmed, and Dr. Zuhdi Jasser, a whose Center for counters motifs of Jihadist totalitarianism with positive messages—to name a few [45]. Their examples should be lauded and emulated as they help to “melt the bottom of the pyramid” of the iceberg. [SEP] Justify:

Output: The text contrasts with the claim as it discusses concepts such as positive deviance and the influence of high-risk individuals on populations without providing evidence that AI can predict or prevent health issues. It suggests that high-risk individuals can serve as role models and that prevention is rooted in sociocultural factors rather than an AI's ability to predict health outcomes.


Input: Task: pass the claim using the given text. Claim: Certain researchers argue that the properties of proteins can predict their functions accurately. [SEP] Text: First, we used to identify all papers citing each original study. Second, we performed a “similar 2015. We captured the identity of all authors of the obtained 12. 3% (329) of invitations bounced, and 1. 57% (42) actively declined. Assuming that all nonbounced invitations sent were actually received by our targets, 6% (138) of invited experts forecasted at least 1 study. Because novice invites were circulated by graduate program directors, we cannot calculate response rates for novices. We excluded the data of 1 participant who completed the survey well below our threshold of 7 minutes. We disqualified 12 forecasts for which participants declared knowledge of the replication results. based our queries of reproducibility on mouse tumor growth curves in the first 6 studies planned by RP:CB. We used mouse xenograft experiments because they are believed by many to be the most prognostic of clinical utility. Ideally, we would solicit subjective probabilities (i. e. , forecasts) on whether whole studies reproduced. However, every study contained multiple experiments, and the definition of “reproduction” is itself highly debated [32,33]. As a result, using such an approach would make it impossible to verify the accuracy of forecasts. Instead, we used an approach that minimized the interpretational ambiguity of our questions and the ensuing forecast data. Each experiment had a single effect (treatment versus control) that could be said to represent the main finding of the study. This allowed us to collect predictive judgments for each study and to create objective and unambiguous methods for scoring each prediction. To maintain a mean survey duration of 30 minutes, we created 2 batches of surveys, each asking about 3 RP:CB studies. Survey questions were reviewed and approved by cancer preclinical researcher consultants. For each replication forecast, we gave participants the study title, authors, and links to both the original study and the registered report for the replication. We also gave them the relevant figure from the original paper, with annotations indicating the effect our query centered on. Participants were asked to indicate their subjective probabilities (in percent chance format) that (a) the replication experiments would “also be statistically significant in the same direction (as the original study)” and (b) the effect size of the replication would be “as large or larger than the original effect size. [SEP] Justify:

Output: The text is irrelevant to the claim as it focuses on the methodology used in a study regarding predictions and forecasts without addressing protein properties or their relationship to predicting functions. It does not mention proteins, their properties, or any relevant arguments related to the claim.


Input: Task: corroborate the claim using the given text. Claim: Organic farming often relies on natural fertilizers like compost and manure rather than synthetic chemicals. [SEP] Text: Plant height, stem diameter and number of leaves, including total biomass, root and stem yields (on fresh- and dry-matter bases), all depended on the soil’s contents of the exchangeable bases (particularly exchangeable Ca, i. e. , Ca2+), with a coefficient of determination (R2) in the range of 0. 683-0. 794. Leaf yield of amaranth on a fresh-matter basis depended on soil content of total N (R2 = 0. 776), while leaf yield on a dry-matter basis depended on soil content of Ca2+ (R2 = 0. 850), as with the bulk of the yield indices included in this study. 4. DiscussionThe data attained in this study indicate the agronomic benefit of mixing BSG with a promising animal manure, such as PD, in the appropriate ratio, before composting into organic amendments for application to sandy tropical soils used for organic production of vegetable crops. Composted BSG+PD(1:1), unlike the other treatments, always produced better results than the control wherever treatment had effects, with stem diameter as an exception. A similar trend prevailed for the residual effects of treatment. The PD enriches the soil with SOM and most plant nutrients compared with other types of animal manure (Afriyie et al. , 2013; Chukwuma et al. , 2024). Therefore, its complementing BSG in the compost used would largely explain the results. Taller plants in composted BSG+PD(1:1) than the control for both immediate and residual effects of treatment suggest the presence of some growth-promoting substances such as cytokinin, indole-3-acetic acid (IAA), and gibberellic acid (GA3) in BSG-based organic amendments (Miezah et al. , 2008), which can elongate plant stems and increase the growth of plants. [SEP] Justify:

Output: The text corroborates the claim by discussing the agronomic benefit of using composted materials such as animal manure and byproducts—specifically, the combination of brewers' spent grain (BSG) and poultry manure (PD)—as organic amendments. It emphasizes that these natural fertilizers enrich the soil and promote plant growth, aligning with the idea that organic farming relies on natural rather than synthetic fertilizers.