Input: Task: contrast the claim using the given text. Claim: Deforestation contributes to habitat loss and climate change. [SEP] Text: 3 Relative frequency, relative density and relative dominance were determined following Phillips4 while importance value index (IVI) was calculated following Mishra. 5 Species diversity was determined following Shannon and Wiener information function6 and species similarity index. 7 The study was to see the present state of vegetation in each forest type and a change matrix was prepared to compare the present status of the forests with the original vegetation as described by Champion et al. 1,8 Quality of forest cover The forest cover is being monitored in India since 1985 when the first State of was published by the FSI. Though the forest and tree cover has been increasing marginally after every assessment report which is due apart from steps taken for afforestation and expansion of tree cover on private and common lands is also the result of changes in technology of assessment over the year. Nevertheless, it is credible for the country of such a huge population that the forest cover is increasing as also its flagship wild life species like Lions and Tigers. There is a total of 7082 million tonnes of carbon in India’s forests indicating an increase of 38 million tonnes over the last assessments of 2015. The question from the point of view of ecological stability and sustainability of forests wealth, however, is whether the forests of the country are in good shape quality wise and able to meet the ecological needs of the country. The answer is a firm no despite some remarkable but fragmentary achievements. The degraded forests of less than 40% crown density as per the latest estimation is 30 million ha which has increased from 24 million ha as estimated in 1985 report of the FSI. The moderately dense forests with crown density of more than 40% now stand to 39 million ha which is an addition of around 2 million ha over the 37 million ha reported previously in 1985. This also includes around 9 million ha area of dense forests of more than 70 % crown density. It is these areas which also have most of the wild life and Sanctuaries covering around 15 million ha of the forests. This meagre addition of 2 million ha seems more to be the result of technology rather than improvements in the forest stands. There are 170,000 villages in the country in and around 32 million ha of forests. It is the pressure exerted by the people y these villages for fuel wood, fodder and (NTFPs) living in and around forest areas that the degradation of the forest resources is continuing. [SEP] Justify:

Output: The text contrasts the claim by indicating that despite some marginal increases in forest cover, the overall quality of forests is deteriorating, and forest degradation continues due to human pressure. It highlights that the degraded forests in India amount to 30 million hectares, which implies habitat loss, and indirectly suggests issues related to climate stability, thus contesting the notion that deforestation is solely linked to overall loss without mentioning the and degradation aspect.


Input: Task: pass the claim using the given text. Claim: CRISPR technology enables precise gene editing. [SEP] Text: Skip to Content eLife home page your research Search by keyword or author Reset form my search to Research 10. 7554/eLife. 44452 Open access Copyright information Version of RecordJuly 9, 2019 Open annotations (there are currently 0 annotations on this page). 4,597 views 705 downloads 82 4452. Copy to clipboard Download BibTeX Download. RIS Full text Figures and data Peer review Side by side Additional files 8 figures, 1 table and 3 additional files 1 with 2 supplements Download asset Open asset Defective autophagy enhances RIPK1-dependent and independent necroptosis. (A, B) Cell death assayed by (PI) staining and live-cell imaging for 12–16 hr (n = 5). BMDMs from mice of the indicated genotypes were treated with combinations of TNF/zVAD/Nec-1 (A) or PolyI:C/zVAD/Nec-1 and LPS/zVAD/Nec-1 (B). (C) Immunoblots confirming deletion of autophagy genes in BMDMs of indicated genotypes using RNP electroporation. NTC = non targeting control gRNA. (D, E) Cell death assayed under combinations of PolyI:C/zVAD/Nec-1 (D) or LPS/zVAD/Nec-1 (E) treatment (n = 4). Data in (A, B) are representative of four independent experiments; (C–E) are representative of two independent experiments. *p<0. 05, **p<0. 01, ***p<0. 001, ****p<0. 0001. Bar graphs depict mean. Figure 1—source data 1 Defective autophagy enhances RIPK1-dependent and independent necroptosis. Download elife-44452-fig1-data1-v1. xlsx Figure 1—figure supplement 1 Download asset Open asset Elevated cell death and cytokine production by Atg16l1-c. (A) Cell death assayed by PI staining and live-cell imaging for 12–16 hr following with combinations of Pam3CSK4/zVAD/Nec-1, R848/zVAD/Nec-1 or CpG-ODN 1826/zVAD/Nec-1 (n = 5). [SEP] Justify:

Output: The text does not address or provide any information on CRISPR technology or its ability for precise gene editing. It discusses other topics related to cellular experiments, specific treatments, and results, making it irrelevant to the claim.


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

Output: The text corroborates the claim by discussing how climate change has contributed to an increase in agricultural droughts due to evapotranspiration increases, which suggests a relationship between climate change and extreme weather events. Furthermore, it mentions that the physical mechanisms behind climatic events like atmospheric rivers are changing, which ties back to the concept of climate change influencing specific weather phenomena. The mention of varying impacts of climate change on extreme weather types supports the claim that climate change is affecting weather systems globally.


Input: Task: pass the claim using the given text. Claim: Deforestation contributes to habitat loss and climate change. [SEP] Text: 5 and RCP8. 5 scenarios, assessed by the Maxent simulations. We assigned rankings to species based on IUCN threat categories, taking into account also the future habitat loss. For the calculations, the core-area zonation (CAZ) approach was employed to determine the high-priority areas. This complementarity-based prioritization algorithm assigns conservation values by maximizing regional diversity and its complementarity. Essentially, CAZ emphasizes the selection of areas of high-quality habitats for the rarest or high-weighted species, and the prioritization aims to retain core areas for all species. To ensure that climatic refugia would be identified outside the urbanized and agricultural landscape, we excluded spatial surfaces of land use (cites and cropland) as a conditions mask layer. Moreover, the land cover classes (barren lands, lakes, grasslands, forests, and shrublands) were used as condition layers. These raster layers were derived from the global land cover change maps of the Agency (EEA 2023). We included in the analyses the already existing protected areas (PA), sourced by the Protected Planet: on (UNEP-WCMC and IUCN 2023). As conservation planning due to resource limitations rarely allows all potential habitats’ protection, the threshold used to select the highest priority areas was set to 20% of land as climatic stabilization areas based on the recommendation proposed by the for Nature (Dinerstein et al. 2019). To determine each species’ climatic niche’s representation within its associated PA climate space, we calculated the proportion of its bivariate density grid covered by the PA density grid in QGIS. ResultsCurrent distributional patternsThe predictive accuracies of all models under current conditions were relatively high (AUC > 0. 961), indicating the high reliability of the predictions (Table 1). The predictions properly described the current range for most of the taxa; however, potential distribution appeared slightly broader than their geographic range in the Hyrcanian ecoregion (Fig. 1 and Fig. 2 1). Some of them exceeded their potential niches by areas with at least 25–50% habitat suitability outside the main center of distribution (Fig. 1 1). [SEP] Justify:

Output: The text discusses conservation planning, species distribution, and habitat suitability without explicitly addressing the relationship between deforestation, habitat loss, and climate change. Therefore, the information provided does not corroborate or contrast the claim, making it irrelevant.


Input: Task: pass the claim using the given text. Claim: CRISPR technology enables precise gene editing. [SEP] Text: (B, C) ELISA measurements of IL-1β (B) and TNFα (C) in cell culture supernatants following treatment with combinations of LPS/zVAD/Nec-1 for 18 hr (n = 5). Data in (A) are representative of four independent experiments; (B, C) are representative of two independent experiments. *p<0. 05, **p<0. 01, ***p<0. 001, ****p<0. 0001. Bar graphs depict mean. Figure 1—figure supplement 1—source data 1 Elevated cell death and cytokine production by Atg16l1-c. Download elife-44452-fig1-figsupp1-data1-v1. xlsx Figure 1—figure supplement 2 Download asset Open asset -mediated deletion of genes in primary BMDMs. (A) Schematic of screening protocol to identify conditions for high efficiency eGFP deletion in monocytes and BMDMs using electroporation ofCas9-guide RNA(gRNA) ribonucleoprotein (RNP) complexes. (B) Flow cytometry plot demonstrating condition resulting in highly efficient eGFP loss. (C) Schematic illustrating -mediated deletion of Ptprc/CD45. (D) Flow cytometry plots depicting Ptprc deletion and associated quantification of CD45 knockdown pooled from two independent experiments. Selected electroporation conditions were repeated at least three times with consistent results. Bar graphs depict mean. NTC = non targeting control gRNA. Figure 1—figure supplement 2—source data 2 -mediated deletion of genes in primary BMDMs. Download elife-44452-fig1-figsupp2-data2-v1. xlsx Figure 2 with 2 supplements Download asset Open asset RIPK3, MLKL and TRIF are required for RIPK1-independent necroptosis in Atg16l1-deficient BMDMs. (A-E) Immunoblot (A, C) and cell death assays (B, D, E) of BMDMs from mice of indicated genotypes treated with combinations of LPS/zVAD/Nec-1 following -mediated deletion of RIPK3, MLKL or GSDMD (A, B) (n = 4) or TRIF (C–E) (n = 6). [SEP] Justify:

Output: The text does not address the claim regarding CRISPR technology or its ability to enable precise gene editing. Instead, it focuses on experimental measurements and results related to cytokine production and gene deletion in monocytes and BMDMs, without mentioning CRISPR or its functionalities.


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

Output: The text corroborates the claim by providing detailed evidence of how climate change has increased flood depth and the area affected by flooding in Houston. It states that a 19% increase in precipitation, attributable to human-influenced climate change, resulted in significant additional flood water levels and expanded flood areas. Furthermore, it discusses the estimated probability of severe hurricane losses being quadrupled due to these changes. This evidence supports the claim that climate change is leading to more extreme weather events, specifically through the example of increased flooding.


Input: Task: pass the claim using the given text. Claim: Deforestation contributes to habitat loss and climate change. [SEP] Text: Similarly, the potential niches of sub-endemic species, Euonymus velutinus, Lonicera floribunda, and Quercus castaneifolia, were much broader than the realized ones (Fig. 1 1). Table 1 Predictive performance of the species distribution models (SDMs) evidenced by the area under the curve (AUC) values and altitude changes for the Hyrcanian endemic and sub-endemic species at future climatic scenarios (RCP; ca. 2071–2100); (“ − ” decreasing of elevation) Full size tableThe climatic factors were more important in determining taxa distribution than topography and soil (Table S3). At the regional level, the most limiting factors were the precipitation of the driest month (bio14), the precipitation of the coldest quarter (bio19), and temperature seasonality (bio4). Specifically, the precipitation of the driest month (bio14) had a relatively highest contribution, ranging from 18% to 33% in all tested taxa, except for lowland species. julibrissin and Gleditsia caspica, the potential niches were determined mostly by the temperature seasonality (bio4), reaching nearly 27% of contribution in the simulations, and the precipitation of the coldest quarter (bio17; 17% and 28%, respectively), while for Parrotia persica, only bio17 was more significant with a contribution of ca. 34%. In most of the montane taxa except for Hedera pastuchovii and Ruscus hyrcanus and in lowland Populus caspica, the precipitation of the coldest quarter (bio19) was defined also as the most important variable limiting the distributional patterns. The sum of monthly mean temperatures greater than 0 °C had relatively moderate effects on the distributional patterns with a contribution of > 10% in Acer velutinum, Populus persica, and Ruscus hyrcanus (Table 3 2). The synthetic Emberger’s pluviothermic quotient, evapotranspiration (annualPET), and drought indicators (aridity index “aridityIndex” and relative wetness to aridity “climaticMoistureIndex”) had a negligible contribution in all models. [SEP] Justify:

Output: The text is irrelevant to the claim as it discusses the distribution models of certain plant species and climatic factors that influence their distribution, without mentioning deforestation, habitat loss, or climate change. It focuses on climate variables and their effects on species, which do not directly support or contrast the claim regarding deforestation.


Input: Task: pass the claim using the given text. Claim: CRISPR technology enables precise gene editing. [SEP] Text: Cell death assayed by PI staining and live-cell imaging for 12–16 hr. Data in (A, B) are representative of three independent experiments; (C, D, E) are representative of four independent experiments. **p<0. 01, ***p<0. 001, ****p<0. 0001. Bar graphs depict mean. NTC = non targeting gRNA. Figure 2—source data 1 RIPK3, MLKL and TRIF are required for RIPK1-independent necroptosis in Atg16l1-deficient BMDMs. Download elife-44452-fig2-data1-v1. xlsx Figure 2—figure supplement 1 Download asset Open asset RIPK3 and MLKL drive RIPK1-dependent, TNF-mediated necroptosis; TRIF drives RIPK1-independent, PolyI:C-mediated necroptosis in Atg16l1-c. (A) Cell death assayed by PI staining and live-cell imaging for 12–16 hr of BMDMs treated with combinations of TNFα/zVAD/Nec-1 following -mediated deletion of Ripk3, Mlkl or Gsdmd (n = 4). Gene deletion confirmed by immunoblots in Figure 2A. (B) Immunoblots confirming -mediated deletion of Nlrp3 or Pycard in wild-type or Atg16l1-c. (C) Cell death assayed by PI staining and live-cell imaging for 12–16 hr following -mediated deletion of Nlrp3 or Pycard and treatment with PolyI:C/zVAD/Nec-1 or LPS/zVAD/Nec-1 (n = 5). Data in(A) are representative of three independent experiments; (B, C) are representative of two independent experiments. Bar graphs depict mean. *p<0. 05, **p<0. 01, ****p<0. 0001. NTC = non targeting gRNA. Figure 2—figure supplement 1—source data 1 RIPK3 and MLKL drive RIPK1-dependent, TNF-mediated necroptosis; TRIF drives RIPK1-independent, PolyI:C mediated necroptosis in Atg16l1-c. [SEP] Justify:

Output: The text does not address or provide any information related to CRISPR technology or gene editing. It discusses experimental data related to cell death assays and specific gene deletions, but does not mention CRISPR or its applications in precise gene editing. Therefore, it is irrelevant to the claim.


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

Output: The text corroborates the claim by stating that 'human-induced climate change is already affecting many weather and climate extremes in every region across the globe.' This directly supports the assertion that climate change is resulting in more extreme weather events worldwide.


Input: Task: contrast the claim using the given text. Claim: Deforestation contributes to habitat loss and climate change. [SEP] Text: However, because contemporary climate change has a different trajectory, past performance as refugia does not necessarily guarantee that these areas will offer suitable habitats in the future (Barrows et al. 2020; Keppel et al. 2015; Sandel et al. 2011). The palaeoenvironmental and palynology data concurrently point to the Hyrcanian ecoregion as a long-time glacial refugial area (Connor and Kvavadze 2009; Leroy and Arpe 2007), acting as a sanctuary for the Neogene flora. Currently, the region is relatively buffered from contemporary climate change that enables the persistence of the unique relict ecosystems with high species richness and endemism. Nevertheless, our projections suggest that the climatically suitable habitats for endemic and sub-endemic woody taxa in the Hyrcanian forests are expected to contract by 2100, with a mean projected loss of up to 45%, as generally predicted for other major temperate forest trees in the ecoregion (Dering et al. 2021; Naqinezhad et al. 2022; Sękiewicz et al. 2022; Taleshi et al. 2019). Notably, according to our SDMs, a range shift to the western part of the region is predicted for most species. Specifically, we found that a considerable loss of suitable habitats for endemic woody taxa would be expected in the eastern parts of the region (Golestan) and in the (northwestern Hyrcania) with over 85% and 34%, where the highest species richness is currently observed (Fig. 3A). Although most of the mountainous areas of Gilan are likely to be lost with habitat shifts eastward were predicted in this subregion. The eastern Hyrcanian ecoregion is currently quite different in terms of climatic regimes, with the highest mean temperature and lowest precipitations (Fig. 1B), and the mean annual temperature would be more adversely impacted in the region in the coming decades with increases of even 4 °C. Consequently, these changes may put the local stands beyond the species’ ecological optimum. At the same time, in Gilan, higher precipitation is expected compared to the remaining part of the region which leads to probable range expansion of species occurring in alluvial and lowland sites, such Populus caspica and Alnus glutinosa. [SEP] Justify:

Output: The text contrasts the claim by detailing the specific climatic impacts on habitats in the Hyrcanian ecoregion due to contemporary climate change and its implications for local flora. It mentions projections of a significant loss (up to 45%) of climatically suitable habitats for endemic woody taxa by 2100, indicating that habitat loss may occur due to climate factors, rather than directly linking these changes to deforestation.


Input: Task: pass the claim using the given text. Claim: CRISPR technology enables precise gene editing. [SEP] Text: Download elife-44452-fig2-figsupp1-data1-v1. xlsx Figure 2—figure supplement 2 Download asset Open asset TNF and interferon license necroptosis in BMDMs. (A-F) Cell death assayed by PI staining and live-cell imaging for 12–16 hr of Atg16l1-WT and Atg16l1-cpre-treated with TNFR2-Fc or α-IFNAR1 followed by TLR ligand or TNF mediated necroptosis (n = 5). Cells were pre-treated for 36 hr with 20 μg/mL α-Ragweed, TNFR2-Fc or α-IFNAR1 prior to addition of TLR ligands or TNF. (G) Immunoblots for phosphorylated STAT1 in BMDMs following LPS/zVAD treatment over 6 hr. Data in (A–F) are representative of four independent experiments; (G) are representative of two independent experiments. **p<0. 01, ****p<0. 0001. Bar graphs depict mean. Figure 2—figure supplement 2—source data 2 TNF and interferon license necroptosis in BMDMs. Download elife-44452-fig2-figsupp2-data2-v1. xlsx Figure 3 Download asset Open asset Loss of Atg16l1 drives accumulation of detergent insoluble, high molecular weight 1, RIPK3 and enhances RIPK1/RIPK3 phosphorylation. (A, B) Immunoblots of TRIF in Atg16l1-WT and Atg16l1-clysates following 4 hr of treatment with indicated combinations of LPS/zVAD/Nec-1 and enrichment of NP-40 soluble (A) or insoluble (B) fractions. (C, D) immunoblots for autophosphorylated RIPK1 (Ser166/Thr169, p-RIPK1) and total RIPK1 in Atg16l1-WT and Atg16l1-clysates following 4 hr of treatment with indicated combinations LPS/zVAD/Nec-1 and enrichment of NP-40 soluble (C) or insoluble (D) fractions. [SEP] Justify:

Output: The text does not provide information relevant to the claim about CRISPR technology or its abilities in gene editing. It discusses experimental data related to necroptosis and various immunoblot analyses without mentioning CRISPR or gene editing.


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

Output: The text corroborates the claim by discussing developments in attribution science that directly connect human influence to various types of extreme weather events, such as heat waves and heavy precipitation. It mentions that attribution statements have extended to individual extreme weather events, reinforcing the notion that climate change is causing an increase in these events. Additionally, the text notes that the maturation of attribution methods can help inform the public about the dangers of climate change, aligning with the claim that changing climate patterns lead to more extreme weather events.


Input: Task: pass the claim using the given text. Claim: Renewable energy sources can reduce reliance on fossil fuels. [SEP] Text: Akadémiai Kiadó. (Letöltve: 2024. 11. 04. : on Investment (EROI), fosszilis energiahordozók, megújuló energiaforrások, fenntarthatóság Jegyzet elhelyezéséhez, kérjük, lépj be. ! HivatkozásokVálaszd ki a számodra megfelelő hivatkozásformátumot:Harvard (2024): Magyar Tudomány 2024/04. : Akadémiai Kiadó. Letöltve: (2024. 11. 04. )Chicago. 2024. Magyar Tudomány 2024/04. : Akadémiai Kiadó. (Letöltve: 2024. 11. 04. (2024). Magyar Tudomány 2024/04. Akadémiai Kiadó. (Letöltve: 2024. 11. 04. : on Investment (EROI), fossil fuels, renewable energy sources, sustainability Jegyzet elhelyezéséhez, kérjük, lépj be. ! HivatkozásokVálaszd ki a számodra megfelelő hivatkozásformátumot:Harvard (2024): Magyar Tudomány 2024/04. : Akadémiai Kiadó. Letöltve: (2024. 11. 04. )Chicago. 2024. Magyar Tudomány 2024/04. : Akadémiai Kiadó. (Letöltve: 2024. 11. 04. (2024). Magyar Tudomány 2024/04. Akadémiai Kiadó. (Letöltve: 2024. 11. 04. : 10. 1556/2065. 185. 2024. 4. 8 Jegyzet elhelyezéséhez, kérjük, lépj be. ! [SEP] Justify:

Output: The text is largely composed of citation guidelines and references related to the publication without addressing the claim directly. It does mention 'fossil fuels' and 'renewable energy sources'; however, it does not provide any meaningful information that could corroborate or contrast the claim. Thus, the text is irrelevant to the claim about renewable energy reducing reliance on fossil fuels.


Input: Task: pass the claim using the given text. Claim: CRISPR technology enables precise gene editing. [SEP] Text: (E, F) immunoblot assay for autophosphorylated RIPK3 (Thr231/Ser232, p-RIPK3) and total RIPK3 in Atg16l1-WT and Atg16l1-clysates following 4 hr of treatment with indicated combinations of LPS/zVAD/Nec-1 and enrichment of NP-40 soluble (E) or insoluble (F) fractions. Representative data shown from three independent experiments. In all immunoblots, -mediated TRIF deletion was performed in Atg16l1-cfollowed by LPS/zVAD treatment as a negative control. *=non specific bands (n. s. ). Figure 4 with 2 supplements Download asset Open asset Overabundance of TRIF, phosphorylated and ubiquitinated RIPK1 and RIPK3 coincides with accelerated necroptosis of Atg16l1 deficient BMDMs. (A) Kinetic measurement of cell death over 18 hr of LPS/zVAD treatment (n = 5). (B) Immunoblot of TRIF in NP-40 insoluble fractions of BMDM lysates over 6 hr of LPS/zVAD treatment. (C, D) Immunoblots of autophosphorylated and total RIPK1 (C), RIPK3 (D) in NP-40 insoluble fractions of BMDM lysates treated as in (B). (E) Immunoblots of autophosphorylated RIPK1, RIPK3 and ubiquitin in BMDM lysates following immunoprecipitation of M1 or K63-ubiquitinated proteins after 4 hr of LPS/zVAD treatment. Data in (A) are representative of four independent experiments; (B–D) are representative of three independent experiments; (E) are representative of three independent experiments. *=P < 0. 05. Figure 4—source data 1 Overabundance of TRIF, phosphorylated and ubiquitinated RIPK1 and RIPK3 coincides with accelerated necroptosis of ATG16L deficient BMDMs. Download elife-44452-fig4-data1-v1. [SEP] Justify:

Output: The text does not address the claim regarding CRISPR technology or its applications in gene editing. Instead, it discusses immunoblot assays and specific proteins related to necroptosis in the context of BMDMs. Therefore, it is irrelevant to the claim.


Input: Task: corroborate the claim using the given text. Claim: Deforestation contributes to increased atmospheric CO2 levels. [SEP] Text: 4) Most of the emitted IR radiation is leaving the atmosphere, but a part of it (back radiation or backscatter) from greenhouse gases returns to the Earth’s surface and is absorbed. 5) The absorbed backscatter leads to increased surface temperature that heats the air. 6) Humans’ increased emission of greenhouse gases, mainly CO2, leads to an enhanced Greenhouse Effect. This explanation is used by IPCC (on Climate Change) [3] and other research [4] [5] [6]. Points 1 to 4 have been verified by several types of measurements, both by satellites and at ground level [7] [8]. However, no direct measurement was made of the resulting heating of Earth’s surface. IPCC admits that the amount of heating is still discussed and that the enhanced greenhouse effect from increased amount of CO2 has, until recently, only been confirmed by empirical evidence [9]. But one experiment, clearly showing that CO2 can heat a black-body, was performed by Harde and Schnell in 2020 [10]. This experiment was the basis for the experiments presented here. 2. The Harde/Harde and Schnell [10] have presented an experiment that should explain how added amounts of greenhouse gases (like CO2) heat the surface of the Earth. Their experimental setup is shown in Figure 1, consisting of a cylinder-shaped tank, which on the inside consists of polished aluminum. Internal height/diameter is 111 cm/36cm. The doom shaped top part is heated to 30˚C while a cooled (−11. 4˚C), black plate is placed at the bottom. Compared to the earth/atmosphere situation this setup is mounted upside-down. Close to the top of the tank is a small black-painted aluminum plate placed, representing the Earth’s surface (the EP). This setup leads to a vertically stable temperature gradient, similar to the lapse rate gradient of the troposphere. The cold plate represents the top of the troposphere. The cylinder was first filled with dry air and left to stabilize thermally. When CO2 was added to the air in the tank the temperature of the increases. This is seen in their Figure 10(a). The highest concentration of CO2 used Figure 1. The experimental setup used by Harde and Schnell [10]. was 20%, leading to an increase of the temperature of 1. 18˚C. [SEP] Justify:

Output: The text corroborates the claim by explaining the relationship between increased CO2 emissions and the enhanced greenhouse effect. It details how added amounts of greenhouse gases like CO2 can lead to heating the Earth's surface, which correlates to the impacts of deforestation that result in higher atmospheric CO2 levels. The mention of empirical evidence supporting the idea that CO2 can heat the Earth further strengthens the assertion that contributing factors like deforestation influence CO2 levels in the atmosphere.


Input: Task: pass the claim using the given text. Claim: Renewable energy sources can reduce reliance on fossil fuels. [SEP] Text: , 2022). Az energiaszektor átalakítása során az egyik fontos mutatószám az EROI, azaz az energiabefektetés-energiahozam arány, amely lehetővé teszi a különböző energiaforrások és technológiák összehasonlítását, és segíti a döntéshozókat abban, hogy optimális energiastratégiákat alakítsanak ki a jövőbeli energiabiztonság és fenntarthatóság biztosítása érdekében. Az EROI egy dimenzió nélküli mutató. Értéke azt mutatja, hogy az adott energiaforrás vagy technológia mennyi többletenergiát hoz létre a befektetett energiához képest. Amikor ez az érték 1 feletti, az azt jelenti, hogy az energiatermelés hatékonyabb és eredményesebb, mivel több hasznosítható energia jön létre az adott befektetett energiához képest. Amennyiben viszont az értéke kisebb mint 1, akkor az energiaforrás vagy technológia nem hatékony, mert kevesebb hasznosítható energia keletkezik, mint amennyit annak előállításához felhasználtak (Hall et al. , 2014; Court–Fizaine, 2017; Brockway et al. , 2019; de Castro–Capellán-Perez, 2020; Diesendorf–Wiedmann, 2020). [SEP] Justify:

Output: The text discusses the Energy Return on Investment (EROI) in relation to energy sources and their efficiency but does not directly address the claim about renewable energy sources reducing reliance on fossil fuels. It focuses on energy yield in comparison to the energy invested, which is somewhat relevant but does not specifically corroborate or contrast with the claim.


Input: Task: pass the claim using the given text. Claim: CRISPR technology enables precise gene editing. [SEP] Text: xlsx Figure 4—figure supplement 1 Download asset Open asset Enhanced MLKL activation and accelerated cell death in Atg16l1 deficient BMDMs following LPS- or PolyI:C-mediated necroptosis. (A) Immunoblots depicting p-MLKL Ser345 in NP-40 soluble and insoluble fractions of BMDM lysates 4 hr after indicated treatments. (B, C) Death of wild-type and Atg16l1-cassayed by PI staining and live-cell imaging over 18 hr of LPS- (B) or PolyI:C- (C) mediated necroptosis. LPS +zVAD time-course is same as in Figure 4A. Data in (A) are representative of three independent experiments; (B, C) are representative of four independent experiments. Dots represent mean (n = 5)±S. D. *p<0. 05, **p<0. 01, ****p<0. 0001. Figure 4—figure supplement 1—source data 1 Enhanced MLKL activation and accelerated cell death in ATG16L1 deficient BMDMs following LPS- or PolyI:C-mediated necroptosis. Download elife-44452-fig4-figsupp1-data1-v1. xlsx Figure 4—figure supplement 2 Download asset Open asset Lysosomal function and autophagic flux drive turnover of active 1 and RIPK3 during necroptosis. (A-C) Immunoblots assaying levels of TRIF (A), RIPK1 (B) or RIPK3 (C) in total lysatse (bottom) and detergent- insoluble fractions (top) of BMDM lysates over 6 hr of LPS/zVAD treatment in the presence of Bafilomycin A1. (D–F) Immunoblots assaying basal turnover of TRIF (D), RIPK1 (E) or RIPK3 (F) by perturbation of proteasomal (MG132, 2 μM) or lysosomal (Bafilomycin A1, BafA1 100 nM) activity. Dot plots in (D–F) summarize protein abundance measured by immunoblot intensity normalized to 0 hr time point. Lines depict mean (n = 4). [SEP] Justify:

Output: The text does not address the claim regarding CRISPR technology or its capabilities in gene editing. Instead, it discusses experimental results related to necroptosis and various protein assays, which are unrelated to the topic of CRISPR or gene editing precision.