--- tags: - sentence-transformers - sentence-similarity - feature-extraction - dense - generated_from_trainer - dataset_size:2993 - loss:MultipleNegativesRankingLoss base_model: intfloat/e5-large-v2 widget: - source_sentence: 'query: đŸ€Ż Without carbon dioxide, life on Earth wouldn''t exist. #ClimateChange #ScienceFacts' sentences: - 'passage: With a view on the present discussions on the greenhouse effect and the role of COz and CH 4 in the changes of the Earth''s atmosphere and climate, the knowledge about the carbon budget in the history of the Earth provides a solid basis. The present scope on the evolution of the Earth''s crust and atmosphere is of course an extrapolation of present day processes and interactions. We are sure that the evolution of the atmosphere is intimately linked to the evolution of life. Without the existence of life, the atmosphere of the Earth would equal the atmosphere of Venus or Mars, consisting of about 95% CO2, 3% N 2, and almost negligible amounts of noble gases and oxygen. The change from an oxygen-poor, CO 2rich to a CO2-poor and oxygen-rich atmosphere is due to autotrophic CO 2 fixation driven by photosynthesis. The ongoing processes are summarized in the well-known carbon cycle (Fig. 1). The amounts of' - 'passage: Greenhouse gases (GHGs) other than carbon dioxide (CO2) play an important role in the effort to understand and address global climate change. Approximately 25% of Global warming potential-weighted GHG emissions in the year 2005 comprise the non-CO2 GHGs. The report, Global Mitigation of Non-CO2 Greenhouse Gases: 2010–2030 provides a comprehensive global analysis and resulting data-set of marginal abatement cost curves that illustrate the abatement potential of non-CO2 GHGs by sector and by region. The basic methodology – a bottom-up, engineering cost approach – builds on the baseline non-CO2 emissions projections published by EPA, applying abatement options to the emissions baseline in each sector. The results of the analysis are MAC curves that reflect aggregated breakeven prices for implementing abatement options in a given sector and region. Among the key findings of the report is that significant, cost-effective abatement exists from non-CO2 sources with abatement options that are available today. Without a price signal (i.e. at $0/tCO2e), the global abatement potential is greater than 1800 million metric tons of CO2 equivalent. Globally, the energy and agriculture sectors have the greatest potential for abatement. Among the non-CO2 GHGs, methane has the largest abatement potential. Despite the potential for project level cost savings and environmental benefits, barriers to mitigating non-CO2 emissions continue to exist. This paper will provide an overview of the methods and key findings of the report.' - 'passage: Vol. 119, No. 4 NewsOpen AccessBlack Carbon: The Dark Horse of Climate Change Drivers Charles W. Schmidt Charles W. Schmidt Published:1 April 2011https://doi.org/10.1289/ehp.119-a172Cited by:4AboutSectionsPDF ToolsDownload CitationsTrack Citations ShareShare onFacebookTwitterLinked InReddit For decades, efforts to slow global warming have mostly aimed to limit heat-trapping emissions of carbon dioxide (CO2). Now scientists are pointing to a different class of warming agents they say also must be targeted to keep global temperatures in check. Dubbed "short-lived climate forcings" (SLCFs), these other emissions—namely, black carbon particles, methane, hydrofluorocarbons, and tropospheric ozone—are even more powerful than CO2 in terms of their warming potential. But they persist in the atmosphere for much shorter durations than CO2, which can linger airborne for hundreds to thousands of years.1Steve Seidel, vice president for policy analysis at the Pew Center on Global Climate Change, says the recent emphasis on SLCFs represents new policy thinking on climate change. "We thought the Kyoto Protocol and its follow-on agreements would get us to where we need to be, but that''s not working out the way we hoped it would," he says. "So, we''re broadening the discussion and opening up new pathways for going forward."Given the enormity of human emissions, many climate scientists believe CO2 will one day become the dominant force behind climate change. But for now, CO2 and the SLCFs are nearly on par in terms of their climate changing effects, according to Veerabhadran Ramanathan, a professor at The Scripps Institute of Oceanography.In a report published in February 2011, the United Nations Environment Programme (UNEP) called attention to SLCFs, claiming their emissions must be cut together with CO2 in order to prevent global temperatures from crossing a dangerous threshold.2 Doing that would offer health benefits too, UNEP stated, because SLFCs are also toxic air pollutants. Particulate emissions from diesel exhaust—a major source of black carbon—have been linked to lung and heart disease as well as cancer.3 But where it would take a transformation of the energy sector (at a cost of trillions of dollars over multiple decades1) to drop CO2 emissions enough to influence the climate, cutting SLCFs to achieve a similar goal could be achieved with current technologies under policy frameworks that are already in place, such as clean air regulations, according to Seidel.Dark and DirtyAmong the SLCFs, black carbon garners the most attention because its climate and health effects are greater than those of the others, says Mark Jacobson, a professor in the Stanford University Department of Energy Resources Engineering. Evidence on black carbon''s climate impacts has been building since at least the mid-1990s, when Ramanathan and colleague Paul Cruzan, a Nobel prize–winning atmospheric chemist from the Max Planck Institute for Chemistry, first speculated that "brown clouds" laden with the dark particles influence weather patterns over South Asia, a hypothesis that was supported by future research.4But the way black carbon affects the climate is nuanced and hard to study, and it''s only recently that the science has begun to mature to the degree that policies to limit emissions can be proposed on climatic grounds, says Drew Shindell, a scientist with the Goddard Institute for Space Studies at the National Aeronautics and Space Administration (NASA), who led the panel that produced the new report by UNEP. "What we''re seeing now with the UNEP document and other more recent papers are attempts to generate the first cohesive picture of black carbon''s effects on the climate and ways to address it," Seidel says.Spewed into the air by diesel engines, dirty cookstoves, and open burning, black carbon is the material that burns in an orange flame, explains Tami Bond, an affiliate professor of atmospheric sciences at the University of Illinois at Urbana–Champaign. "What you see in fire is black carbon glowing," she says. What escapes to the air from fire, Bond adds, are agglomerated particles of nearly pure carbon, each several thousand times smaller than the width of a human hair.Those particles absorb sunlight in all its wavelengths and transfer its warmth to the atmosphere. With roughly a million times the heat-trapping power of CO2,5 black carbon can travel long distances on air currents. If it falls out with precipitation on snowpack or ice, it absorbs heat and accelerates melting by interfering with how those white surfaces reflect sunlight back to space.6But black carbon is also co-emitted with other particles that reflect more sunlight than they absorb. And these other specks of ash and organic materials have a net cooling effect, such that combustion emissions will warm the air only as much as their black carbon content allows. With a roughly 1:1 ratio of organic7 to black carbon particles, diesel emissions top the list in terms of their climate warming potential, according to Jacobson.Emissions from solid fuel combustion—namely, from cookstoves that burn animal dung, wood, and other types of biomass—follow with a ratio of organic to black carbon particles of 4:1. Open fires tend to smolder and eject a lot of ash particles that reflect sunlight, but even so, they exert a net warming effect on the atmosphere, Jacobson says. On the other hand, emissions from forest fires, with an 8:1 organic to black carbon particle ratio, cool the atmosphere in the short run but lead to warming later because of the massive amounts of CO2 they put into the air, he says.Climatologic ImpactsAbout 77% of the estimated 8,000 kilotons of black carbon emitted globally every year come from the developing world, discharged mainly from cookstoves, open burning, and old diesel engines,8 which means the focus of cleanup lies largely with poorer countries, possibly with the financial and technical support from developed countries, according to Seidel. Wealthier nations such as the United States, on the other hand, emit much less black carbon, and diesel engines account for the vast majority of those emissions.8North Amerian emissions dominate when it comes to the black carbon falling on ice in Greenland, Shindell says, while European emissions dominate what reaches the rest of the Arctic. "The largest black carbon source in both North America and Europe is diesel, so I think it''s safe to say that''s the biggest [contributor from these countries]," he says.As for additional contributions from northern industrialized countries—and Arctic ice sheets are known to be most vulnerable to black carbon emissions from locales north of the 40th parallel8—Shindell also cites forest fires and residential woodstoves and fireplaces. But he emphasizes that the role of black carbon in Arctic melting isn''t fully understood and that much of the ice losses there so far probably result from greenhouse gases.9"What we can say is that black carbon from northern countries is the dominant contributor to darkening of Arctic snow, which is at least partly responsible for melting," he says. "It''s hard to be more definitive as black carbon trends during the last few decades, when melting has accelerated greatly, seem not to be large—roughly flat, really—but we only have data for the Western Hemisphere, and even that is fairly sparse."Unlike greenhouse gases, which float around the planet on long time scales, black carbon travels in the air for only a week or 10 days before it washes out of the atmosphere.2 Its effects are therefore more regional than global, and its influence on the climate results from both its radiative heating effects and its ability to disrupt cloud formation and rainfall.5Daniel Rosenfeld, a professor of atmospheric sciences at the Hebrew University of Jerusalem, says much about black carbon''s influence on weather remains unknown, however. Ordinarily, airborne particulates seed clouds, he explains, but black carbon particles can get hot enough to vaporize water and prevent clouds from forming at all. Cloud losses result in more heating of the ground, Jacobson adds. And that reduces air pressure over land, which draws air currents from areas of higher pressure, resulting in higher windspeeds.But depending on a range of conditions, including the particulate makeup of the pollution and topographical features of the land, particle emissions can also seed clouds made up of unusually small droplets. These clouds don''t coalesce into denser forms that would otherwise fall as rain, Rosenfeld explains. The result is more clouds but less rain than usual, with commensurate impacts on water supplies and agriculture.10The implications of these impacts are a focus of intense research, but in the meantime, Erika Rosenthal, a staff attorney at Earth Justice, says that South Asian monsoons now come roughly two to three weeks earlier than usual, perhaps because of the region''s heavily polluted air.11 "And that''s crucial for farmers who feed a quarter of the world''s population," she says.Still, Rosenfeld cautions that the science in this area is an evolving story. "It''s very difficult for the scientific community to tease out these effects," he says. "We''re trying to distinguish radiative effects from how particles absorb solar rays apart from air pollution''s effects on clouds, precipitation, and evaporative forces. This is a very big challenge in the field."Policy ImplicationsJust how climate-related concerns about black carbon will drive policy remains to be seen. Policy momentum on SLCFs is picking up on certain fronts. UNEP''s 2011 report presents 16 strategies to stanch the flow of SLCFs into the atmosphere, among them capping fugitive methane emissions from industry and agriculture, banning open-field burning of agricultural waste, taking old diesel vehicles off the road, and substituting traditional biomass cookstoves in the developing world with cleaner models. If achieved within the next 20 years, those measures could halve the rate of climate change expected by mid-century while avoiding some 0.7–4.6 million premature deaths that would have resulted from poor air quality, UNEP asserts.2Meanwhile, a task force convened by the Arctic Council, an intergovernmental forum of circumpolar nations, is investigating ways to lower SLCF emissions with an eye toward limiting rates of ice sheet melting in the near term.12 The measures will be identified in a report to be presented at the council''s next ministerial meeting, in Nuuk, Greenland, on 12 May 2011. Finally, the U.S. Environmental Protection Agency (EPA) is set to release a report to Congress in April 2011 detailing sources of black carbon and cost-effective ways to minimize its health and climate impacts. EPA officials declined to comment on the report in advance of publication.According to Seidel, the United Nations Framework Convention on Climate Change isn''t well suited for negotiations on black carbon; "You''re more likely to see this move forward under regional frameworks focused on air quality," he says. As an example, he cites the MontrĂ©al Protocol, which successfully phased out the chlorofluorocarbons that degrade the ozone layer.In the United States, black carbon reductions apply mainly to diesel standards, which have already been tightening since the 1970s in response to health needs. The California Air Resources Board (CARB) led the charge, issuing the first statewide regulation on diesel emissions from heavy trucks in the late 1980s. Since then, regulations have steadily tightened in California,13 and the U.S. EPA has followed suit.14In 2006 the EPA adopted an ultra-low-sulfur diesel requirement for on-road vehicles that dropped allowable concentrations from 500 to 15 ppm, and the agency is now expanding that rule to cover more transportation sources, including off-road vehicles, railroads, and ships. Ultra-low-sulfur diesel fuels end up reducing black carbon emissions because they allow for the use of particulate exhaust filters, which would have been "poisoned" (rendered ineffectual) by sulfates. Since 2007, the EPA has mandated that all new on-road vehicles be equipped with advanced emission controls that require the new cleaner diesel fuels to run properly.Ramanathan''s group recently published a study showing that California''s black carbon emissions dropped 50% over the period 1989–2008.15 (That''s according to measurements collected at 22 sites through California''s Interagency Monitoring of Protected Visual Environments program.) The study results also suggested those reductions were accompanied by a corresponding 50% drop in black carbon''s warming effect (or more specifically, its "radiative forcing") over the whole state of California.But Bart Croes, chief of the CARB Research Division, says there''s no plan to tighten the state''s diesel regulations further in response to climate concerns. "Public health is the major driver behind these regulations, and they appear to have also reduced climate impacts," he says. "So we see no need to modify our regulations [specifically] to address the climate. What we''re doing for public health is also exactly what we should be doing for the climate."California now mandates retrofits to bring all pre-2007 on-road diesel truck and buses in line with current particle emissions regulations. According to CARB calculations, these older vehicles accounted for 95% of all diesel particulate emitted from on-road trucks and buses in California in 2010. The estimated cost to retrofit trucks and buses in the state will be $2.2 billion from 2012 to 2025.16 Of course, estimated costs nationwide are far higher: a 2009 report on black carbon published by the Pew Center on Global Climate Change cited data showing it would cost $32 billion to retrofit 54% of the estimated 5.4 million heavy-duty on-road diesel vehicles in the United States.5That''s a lot of money. But considering that 90% of U.S. black carbon emissions come from the transportation sector, mainly diesel vehicles, it''s also just part of what the nation would have to pay in order to meet UNEP''s aim to install diesel particle filters for on- and off-road vehicles and to eliminate high-emitting on- and off-road vehicles, which are 2 of the 16 strategies identified in its report.2Meanwhile, looking for budget-slashing opportunities, President Obama recently cut 2012 funding for the Diesel Emissions Reduction Program, which gives EPA grant and loan authority to fund the retrofitting or replacement of existing diesel vehicles. The alternative, of course, is to refrain from mandatory retrofitting and take the vehicles off the road through attrition.But that leads to an intriguing question: If—as is the case in California—the United States is unwilling or unlikely to impose further tightening of diesel regulations in response to climate concerns, how does the emerging evidence on black carbon influence environmental policy here? Seidel says there is no evidence that cleaning up diesels in the United States will have the biggest, let alone the most cost-effective, impacts on slowing warming in the Arctic. Yet Rosenthal argues that U.S. contributions to Arctic black carbon pollution constitute an imperative for the country to clean up its diesel emissions faster.But most of the opportunity to reduce emissions are found in the developing world, she adds, where diesel standards aren''t as stringent, and where cookstoves and open burning pose major environmental problems. "The science and policy dilemmas are complicated," Rosenthal says. "But we need to make decisions about this now."More than three-quarters of the world''s black carbon is thought to come from developing countries, discharged from cookstoves, open burning, and older diesel engines. This data visualization uses data from NASA''s GEOS-5 Goddard Chemistry Aerosol and Transport (GOCART) climate model to show atmospheric concentrations of black carbon on 26 September 2009. Aerosol optical thickness ranges nonlinearly from 0.002 (transparent) to 0.02 (purple) to 0.2 (white). Animations of global black soot transport are available at http://tinyurl.com/64nbykb and http://tinyurl.com/69w9s6z.REFERENCES AND NOTES1 Ramanathan V, Victor DGTo Fight Climate Change, Clear the Air. New York Times, Opinion section, online edition27112010. Available: http://tinyurl.com/238we44[accessed 17 Mar 2011]. Google Scholar2 UNEPIntegrated Assessment of Black Carbon and Tropospheric Ozone: Summary for Decision MakersNairobi, KenyaUnited Nations Environment Programme & World Meteorological Association2011. Available: http://tinyurl.com/5vpnapd[accessed 17 Mar 2011]. Google Scholar3 OEHHAAir Toxicology and Epidemiology. Health Effects of Diesel Exhaust: A Fact Sheet by Cal/EPA''s Office of Environmental Health Hazard Assessment and the American Lung AssociationSacramento,CAOffice of Environmental Health Hazard Assessment, California Environmental Protection Agency2007. Available: http://tinyurl.com/67xe2fx[accessed 17 Mar 2011]. Google Scholar4 Ramanathan Vet al.The Indian Ocean experiment and the Asian brown cloud. Curr Sci 83(8):947-955 (2002). Google Scholar5 Bachmann JBlack Carbon: A Science/Policy Primer12Arlington, VAPew Center on Global Climate Change2009. Available: http://tinyurl.com/4pdy5v5[accessed 8 Mar 2011]. Google Scholar6 Doherty SJet al.Black Carbon in Arctic Snow and Its Effect on Surface Albedo. American Geophysical Union, Fall Meeting, 2009 Abstract #A34B-05Washington, DCAmerican Geophysical Union2009. Available: http://tinyurl.com/4dp9qm9[accessed 17 Mar 2011]. Google Scholar7 "Organic carbon" is a term of art referring to organic compounds that contain carbon. Organic carbon is not as black as black carbon, and it absorbs solar heat much less effectively.8 Bice Ket al.Black Carbon: A Review and Policy RecommendationsPrinceton, NJWoodrow Wilson School of Public & International Affairs, Princeton University2009. Available: http://tinyurl.com/6km3yam[accessed 17 Mar 2011]. Google Scholar9 Schmidt CWOut of equilibrium? The world''s changing ice cover. Environ Health Perspect 119(1):A20-A282011.doi:10.1289/ehp.119-a2021196152. Link, Google Scholar10 Jacobson MZShort-term effects of controlling fossil-fuel soot, biofuel soot and gases, and methane on climate, Arctic ice, and air pollution health. J Geophys Res 115:D142092010.doi:10.1029/2009JD013795. Crossref, Google Scholar11 Ramanathan Vet al.Atmospheric Brown Clouds: Regional Assessment Report. SummaryNairobi, KenyaUnited Nations Environment Programme2008. Available: http://tinyurl.com/68r7mpd[accessed 17 Mar 2011]. Google Scholar12 Arctic Council Task Force on SLF Meeting [website]Copenhagen, DenmarkEuropean Environment Information and Observation Network, European Environment Agency(updated 8 Oct 2010). Available: http://tinyurl.com/68zu626[accessed 17 Mar 2011]. Google Scholar13 California Diesel Fuel Program [website]Sacramento, CAState of California Air Resources Board, California Environmental Protection Agency(updated 29 Jun 2010). Available: http://tinyurl.com/67crxbd[accessed 17 Mar 2011]. Google Scholar14 Fuels and Fuel Additives [website]Washington, DCU.S. Environmental Protection Agency(updated 18 Jan 2011). Available: http://tinyurl.com/5taafv8[accessed 17 Mar 2011]. Google Scholar15 Bahadur Ret al.Impact of California''s air pollution laws on black carbon and their implications for direct radiative forcing. Atmos Environ 45(5):1162-11672011.doi:10.1016/j.atmosenv.2010.10.054. Crossref, Google Scholar16 CARBTruck and Bus 2010 [website]. Appendix I: Costs and Cost MethodologySacramento, CAState of California Air Resources Board, California Environmental Protection Agency(updated 3 Mar 2011). Available: http://tinyurl.com/476ekts[accessed 17 Mar 2011]. Google ScholarFiguresReferencesRelatedDetailsCited by Downward G, van der Zwaag H, Simons L, Meliefste K, Tefera Y, Carreon J, Vermeulen R and Smit L (2018) Occupational exposure to indoor air pollution among bakery workers in Ethiopia; A comparison of electric and biomass cookstoves, Environmental Pollution, 10.1016/j.envpol.2017.10.094, 233, (690-697), Online publication date: 1-Feb-2018. Downward G, Hu W, Rothman N, Reiss B, Wu G, Wei F, Xu J, Seow W, Brunekreef B, Chapman R, Qing L and Vermeulen R (2015) Outdoor, indoor, and personal black carbon exposure from cookstoves burning solid fuels, Indoor Air, 10.1111/ina.12255, 26:5, (784-795), Online publication date: 1-Oct-2016. Soneja S, Tielsch J, Khatry S, Curriero F and Breysse P (2016) Highlighting Uncertainty and Recommendations for Improvement of Black Carbon Biomass Fuel-Based Emission Inventories in the Indo-Gangetic Plain Region, Current Environmental Health Reports, 10.1007/s40572-016-0075-2, 3:1, (73-80), Online publication date: 1-Mar-2016. Soneja S, Tielsch J, Curriero F, Zaitchik B, Khatry S, Yan B, Chillrud S and Breysse P (2015) Determining Particulate Matter and Black Carbon Exfiltration Estimates for Traditional Cookstove Use in Rural Nepalese Village Households, Environmental Science & Technology, 10.1021/es505565d, 49:9, (5555-5562), Online publication date: 5-May-2015. Vol. 119, No. 4 April 2011Metrics About Article Metrics Publication History Originally published1 April 2011Published in print1 April 2011 Financial disclosuresPDF download License information EHP is an open-access journal published with support from the National Institute of Environmental Health Sciences, National Institutes of Health. All content is public domain unless otherwise noted. Note to readers with disabilities EHP strives to ensure that all journal content is accessible to all readers. However, some figures and Supplemental Material published in EHP articles may not conform to 508 standards due to the complexity of the information being presented. If you need assistance accessing journal content, please contact [email protected]. Our staff will work with you to assess and meet your accessibility needs within 3 working days.' - source_sentence: 'query: co2 is the most important non-condensing greeenhouse gases' sentences: - 'passage: We modelled the financial and environmental costs of two commonly used anaesthetic plastic drug trays. We proposed that, compared with single-use trays, reusable trays are less expensive, consume less water and produce less carbon dioxide, and that routinely adding cotton and paper increases financial and environmental costs. We used life cycle assessment to model the financial and environmental costs of reusable and single-use trays. From our life cycle assessment modelling, the reusable tray cost (Australian dollars) $0.23 (95% confidence interval [CI] $0.21 to $0.25) while the single-use tray alone cost $0.47 (price range of $0.42 to $0.52) and the single-use tray with cotton and gauze added was $0.90 (no price range in Melbourne). Production of CO2 was 110 g CO2 (95% CI 98 to 122 g CO2) for the reusable tray, 126 g (95% CI 104 to 151 g) for single-use trays alone (mean difference of 16 g, 95% CI -8 to 40 g) and 204 g CO2 (95% CI 166 to 268 g CO2) for the single-use trays with cotton and paper Water use was 3.1 l (95% CI 2.5 to 3.7 l) for the reusable tray, 10.4 l (95% CI 8.2 to 12.7 l) for the single-use tray and 26.7 l (95% CI 20.5 to 35.4 l) for the single-use tray with cotton and paper Compared with reusable plastic trays, single-use trays alone cost twice as much, produced 15% more CO2 and consumed three times the amount of water Packaging cotton gauze and paper with single-use trays markedly increased the financial, energy and water costs. On both financial and environmental grounds it appears difficult to justify the use of single-use drug trays.' - 'passage: Abstract. In this work the three dimensional compressible moist atmospheric model ASAMgpu is presented. The calculations are done using graphics processing units (GPUs). To ensure platform independence OpenGL and GLSL are used, with that the model runs on any hardware supporting fragment shaders. The MPICH2 library enables interprocess communication allowing the usage of more than one GPU through domain decomposition. Time integration is done with an explicit three step Runge-Kutta scheme with a time-splitting algorithm for the acoustic waves. The results for four test cases are shown in this paper. A rising dry heat bubble, a cold bubble induced density flow, a rising moist heat bubble in a saturated environment, and a DYCOMS-II case.' - 'passage: Greenhouse gases (GHGs) other than carbon dioxide (CO2) play an important role in the effort to understand and address global climate change. Approximately 25% of Global warming potential-weighted GHG emissions in the year 2005 comprise the non-CO2 GHGs. The report, Global Mitigation of Non-CO2 Greenhouse Gases: 2010–2030 provides a comprehensive global analysis and resulting data-set of marginal abatement cost curves that illustrate the abatement potential of non-CO2 GHGs by sector and by region. The basic methodology – a bottom-up, engineering cost approach – builds on the baseline non-CO2 emissions projections published by EPA, applying abatement options to the emissions baseline in each sector. The results of the analysis are MAC curves that reflect aggregated breakeven prices for implementing abatement options in a given sector and region. Among the key findings of the report is that significant, cost-effective abatement exists from non-CO2 sources with abatement options that are available today. Without a price signal (i.e. at $0/tCO2e), the global abatement potential is greater than 1800 million metric tons of CO2 equivalent. Globally, the energy and agriculture sectors have the greatest potential for abatement. Among the non-CO2 GHGs, methane has the largest abatement potential. Despite the potential for project level cost savings and environmental benefits, barriers to mitigating non-CO2 emissions continue to exist. This paper will provide an overview of the methods and key findings of the report.' - source_sentence: 'query: New data suggests that Australia''s temps have only risen by 0.3 degrees over the last 100 years, much lower than the 1 degree usually cited.' sentences: - 'passage: The Arctic is warming and melting at alarming rates. Within the lifetime of a Millennial, the volume of ice floating on the Arctic Ocean has declined by at least half. The pace of Arctic warming is two‐to‐three times that of the globe; this disparity reached a new record high during 2016. While the Arctic spans only a small fraction of the Earth, it plays a disproportionate and multifaceted role in the climate system. In this article, we offer new perspectives on ways in which the Arctic''s rapid warming may influence weather patterns in heavily populated regions (the mid‐latitudes) of the Northern Hemisphere. Research on this topic has evolved almost as rapidly as the snow and ice have diminished, and while much has been learned, many questions remain. The atmosphere is complex, highly variable, and undergoing a multitude of simultaneous changes, many of which have become apparent only recently. These realities present challenges to robust signal detection and to clear attribution of cause‐and‐effect. In addition to updating the state of this science, we propose an explanation for the varying and intermittent response of mid‐latitude circulation to the rapidly warming Arctic. WIREs Clim Change 2017, 8:e474. doi: 10.1002/wcc.474 This article is categorized under: Climate Models and Modeling > Knowledge Generation with Models' - 'passage: S (1995) recently reported that temperatures in Ghana were increasing during this century and that the temperature rise could be evidence of a global warming signal. Using data from 11 stations, Stephens shows that the temperatures in the 1961 to 1990 period were higher than temperatures in the 1930 to 1960 period, noting that, between 1945 and 1990, temperatures in Ghana were ''soaring'' upwards; suggested causes included the ''greenhouse'' effect and the potential influences of urbanization. While I commend Stephens for the effort, I conducted the following research that may be of interest to individuals concerned with regional climate changes over the period of reliable historical records. I collected the 1945 to 1994 monthly temperature anomaly data from the widely-used Jones (1994) data-set for the 5° latitude by 5° longitude grid cell that contains most of Ghana (centred on 7.5°N, 2.5°W). A plot of the 12months'' smoothed anomalies (Fig. 1) shows variability from year to year, but absolutely no evidence of any ''quite significant soaring of temperatures''. From 1945 to 1994, the temperatures in this grid cell actually cooled slightly, but at a statistically insignificant rate. From 1945 to 1990, there is simply no warming in the record. The satellite-based lower-tropospheric temperature data developed and described by Spencer & Christy (1990) provides another opportunity for testing temperature trends in Ghana. I collected the updated satellite data for the five 2.5° latitude by 2.5° longitude grid cells that cover Ghana for the period 1979 to 1994, then smoothed the data using a 12-months filter, and plotted the data in Fig. 1. The satellite-based lower-tropospheric temperature data reveal a statistically highly significant cooling of 0.027°C per year over the period of record. Although Ghana represents only 0.05% of the Earth''s surface, it is important to analyse temperature trends even at this spatial scale. Stephens has shown that the temperatures at 11 stations in Ghana have increased since the end of World War II. However, this warming signal does not appear in the widely-used Jones (1994) data and it is certainly not found in the updated satellite-based Spencer & Christy (1990) lower-tropospheric temperature data. 1945 195' - 'passage: S (1995) recently reported that temperatures in Ghana were increasing during this century and that the temperature rise could be evidence of a global warming signal. Using data from 11 stations, Stephens shows that the temperatures in the 1961 to 1990 period were higher than temperatures in the 1930 to 1960 period, noting that, between 1945 and 1990, temperatures in Ghana were ''soaring'' upwards; suggested causes included the ''greenhouse'' effect and the potential influences of urbanization. While I commend Stephens for the effort, I conducted the following research that may be of interest to individuals concerned with regional climate changes over the period of reliable historical records. I collected the 1945 to 1994 monthly temperature anomaly data from the widely-used Jones (1994) data-set for the 5° latitude by 5° longitude grid cell that contains most of Ghana (centred on 7.5°N, 2.5°W). A plot of the 12months'' smoothed anomalies (Fig. 1) shows variability from year to year, but absolutely no evidence of any ''quite significant soaring of temperatures''. From 1945 to 1994, the temperatures in this grid cell actually cooled slightly, but at a statistically insignificant rate. From 1945 to 1990, there is simply no warming in the record. The satellite-based lower-tropospheric temperature data developed and described by Spencer & Christy (1990) provides another opportunity for testing temperature trends in Ghana. I collected the updated satellite data for the five 2.5° latitude by 2.5° longitude grid cells that cover Ghana for the period 1979 to 1994, then smoothed the data using a 12-months filter, and plotted the data in Fig. 1. The satellite-based lower-tropospheric temperature data reveal a statistically highly significant cooling of 0.027°C per year over the period of record. Although Ghana represents only 0.05% of the Earth''s surface, it is important to analyse temperature trends even at this spatial scale. Stephens has shown that the temperatures at 11 stations in Ghana have increased since the end of World War II. However, this warming signal does not appear in the widely-used Jones (1994) data and it is certainly not found in the updated satellite-based Spencer & Christy (1990) lower-tropospheric temperature data. 1945 195' - source_sentence: 'query: The Industrial Revolution was a huge turning point, but it didn''t involve global warming. #ClimateAction #LearnMore' sentences: - "passage: Nitrogen fixation is a biologically catalyzed reaction that converts\ \ dinitrogen gas (N2) to ammonium (NH4+), which can then be utilized to support\ \ autotrophic growth. Early research suggested that N2-fixation in the open ocean\ \ was not a significant source of nitrogen for phytoplankton growthsemi; virtually\ \ all of the nitrogen needed for growth was thought to come from the deep ocean\ \ through mixing and upwelling. A growing body of evidence now suggests that N2-fixers\ \ may be far more ubiquitous in the open ocean than previously thought and that\ \ nitrogen fixation is quantitatively significant in the global nitrogen cycle.\ \ \n \nThis finding is important because primary production supported by N2-fixation\ \ can result in a net export of carbon from the surface waters to the deep ocean\ \ and a net draw-down of atmospheric carbon dioxide and may therefore play a significant\ \ role in the global carbon cycle as well. In fact, N2-fixation may be the only\ \ biologically mediated process in the open ocean that drives a significant net\ \ export of atmospheric carbon dioxide over greater than annual timescales. In\ \ addition, the global balance between N2-fixation and denitrification determines\ \ the degree to which the oceans are nitrogen limited. Thus global warming-induced\ \ changes in N2-fixation could have significant long-term effects on oceanic productivity\ \ and the global carbon cycle. If this is the case, then we must understand the\ \ global controls on N2-fixation and find ways to represent it in models that\ \ are currently being developed to predict future climate." - 'passage: PREDICtion, little noted at the time, that anthropogenic emissions of carbon dioxide would trap the radiative energy of the sun within the earth''s atmosphere and raise surface temperatures. 1 An early investigation of this "greenhouse effect" concluded that a "large-scale geophysical experiment" began ever since the Industrial Revolution wed civilization to fossil fuels. 2 The recent data of several international consortia show that global warming is accelerating at a rate far greater than that predicted a century ago and is due in large part to combustion of fossil fuels. 3 This issue of MSJAMA brings together several lines of published evidence that global warming has emerged as a public health challenge requiring serious, concerted action.Jonathan Patz and Mahmooda Khaliq survey the immediate threats posed by climate change as well as some of the more insidious ones.Kent Bransford and Janet Lai find grounds for a common approach to both climate change and air pollution.Stephen Liang and colleagues describe technologies that can help track the spread of climate-sensitive infectious disease vectors.Finally, William Burns discusses public policy tools to respond and adapt to these challenges.Unfounded alarmism has no place either in clinical practice or in the legislative process.On the other hand, we cannot simply ignore extensive, peer-reviewed data on the causes and impacts of climate change.Lending a sense of urgency to this seemingly distant and abstract threat may well require us to link its consequences to our quality of life.In the absence of domestic leadership on global warming, one way to accomplish this goal might be to summon health care professionals to nontraditional advocacy roles.A similar approach helped give birth to the Montreal Protocol of 1987.Parties to the convention that produced the treaty identified depletion of the UV-absorbing ozone layer by chlorofluorocarbons (CFCs) as a public health threat of potentially catastrophic proportions requiring immediate action, namely, the phasing out of CFCs and related compounds. 4 A role for health care professionals in global environmental policy is a natural extension of a growing ethos of preventive medicine, the sort that has, for instance, reduced the prevalence of smoking in the United States and led to improvements in food, highway, and gun safety.Similarly, it is not too late and none too soon for the health care community to advocate policies that wean us from fossil fuels and ultimately mitigate the extent of human-induced climate change.' - 'passage: Beneath the waves, oxygen disappears As plastic waste pollutes the oceans and fish stocks decline, unseen below the surface another problem grows: deoxygenation. Breitburg et al. review the evidence for the downward trajectory of oxygen levels in increasing areas of the open ocean and coastal waters. Rising nutrient loads coupled with climate change—each resulting from human activities—are changing ocean biogeochemistry and increasing oxygen consumption. This results in destabilization of sediments and fundamental shifts in the availability of key nutrients. In the short term, some compensatory effects may result in improvements in local fisheries, such as in cases where stocks are squeezed between the surface and elevated oxygen minimum zones. In the longer term, these conditions are unsustainable and may result in ecosystem collapses, which ultimately will cause societal and economic harm. Science, this issue p. eaam7240 BACKGROUND Oxygen concentrations in both the open ocean and coastal waters have been declining since at least the middle of the 20th century. This oxygen loss, or deoxygenation, is one of the most important changes occurring in an ocean increasingly modified by human activities that have raised temperatures, CO2 levels, and nutrient inputs and have altered the abundances and distributions of marine species. Oxygen is fundamental to biological and biogeochemical processes in the ocean. Its decline can cause major changes in ocean productivity, biodiversity, and biogeochemical cycles. Analyses of direct measurements at sites around the world indicate that oxygen-minimum zones in the open ocean have expanded by several million square kilometers and that hundreds of coastal sites now have oxygen concentrations low enough to limit the distribution and abundance of animal populations and alter the cycling of important nutrients. ADVANCES In the open ocean, global warming, which is primarily caused by increased greenhouse gas emissions, is considered the primary cause of ongoing deoxygenation. Numerical models project further oxygen declines during the 21st century, even with ambitious emission reductions. Rising global temperatures decrease oxygen solubility in water, increase the rate of oxygen consumption via respiration, and are predicted to reduce the introduction of oxygen from the atmosphere and surface waters into the ocean interior by increasing stratification and weakening ocean overturning circulation. In estuaries and other coastal systems strongly influenced by their watershed, oxygen declines have been caused by increased loadings of nutrients (nitrogen and phosphorus) and organic matter, primarily from agriculture; sewage; and the combustion of fossil fuels. In many regions, further increases in nitrogen discharges to coastal waters are projected as human populations and agricultural production rise. Climate change exacerbates oxygen decline in coastal systems through similar mechanisms as those in the open ocean, as well as by increasing nutrient delivery from watersheds that will experience increased precipitation. Expansion of low-oxygen zones can increase production of N2O, a potent greenhouse gas; reduce eukaryote biodiversity; alter the structure of food webs; and negatively affect food security and livelihoods. Both acidification and increasing temperature are mechanistically linked with the process of deoxygenation and combine with low-oxygen conditions to affect biogeochemical, physiological, and ecological processes. However, an important paradox to consider in predicting large-scale effects of future deoxygenation is that high levels of productivity in nutrient-enriched coastal systems and upwelling areas associated with oxygen-minimum zones also support some of the world’s most prolific fisheries. OUTLOOK Major advances have been made toward understanding patterns, drivers, and consequences of ocean deoxygenation, but there is a need to improve predictions at large spatial and temporal scales important to ecosystem services provided by the ocean. Improved numerical models of oceanographic processes that control oxygen depletion and the large-scale influence of altered biogeochemical cycles are needed to better predict the magnitude and spatial patterns of deoxygenation in the open ocean, as well as feedbacks to climate. Developing and verifying the next generation of these models will require increased in situ observations and improved mechanistic understanding on a variety of scales. Models useful for managing nutrient loads can simulate oxygen loss in coastal waters with some skill, but their ability to project future oxygen loss is often hampered by insufficient data and climate model projections on drivers at appropriate temporal and spatial scales. Predicting deoxygenation-induced changes in ecosystem services and human welfare requires scaling effects that are measured on individual organisms to populations, food webs, and fisheries stocks; considering combined effects of deoxygenation and other ocean stressors; and placing an increased research emphasis on developing nations. Reducing the impacts of other stressors may provide some protection to species negatively affected by low-oxygen conditions. Ultimately, though, limiting deoxygenation and its negative effects will necessitate a substantial global decrease in greenhouse gas emissions, as well as reductions in nutrient discharges to coastal waters. Low and declining oxygen levels in the open ocean and coastal waters affect processes ranging from biogeochemistry to food security. The global map indicates coastal sites where anthropogenic nutrients have exacerbated or caused O2 declines to <2 mg liter−1 (<63 ÎŒmol liter−1) (red dots), as well as ocean oxygen-minimum zones at 300 m of depth (blue shaded regions). [Map created from data provided by R. Diaz, updated by members of the GO2NE network, and downloaded from the World Ocean Atlas 2009]. Oxygen is fundamental to life. Not only is it essential for the survival of individual animals, but it regulates global cycles of major nutrients and carbon. The oxygen content of the open ocean and coastal waters has been declining for at least the past half-century, largely because of human activities that have increased global temperatures and nutrients discharged to coastal waters. These changes have accelerated consumption of oxygen by microbial respiration, reduced solubility of oxygen in water, and reduced the rate of oxygen resupply from the atmosphere to the ocean interior, with a wide range of biological and ecological consequences. Further research is needed to understand and predict long-term, global- and regional-scale oxygen changes and their effects on marine and estuarine fisheries and ecosystems.' - source_sentence: 'query: Apparently, the air a bit higher up isn''t warming as much as the ground level, according to satellite data. đŸ€” #climate #science' sentences: - 'passage: During the Holocene (last 12,000 years) nine cold relapses were observed mainly in the North Atlantic Ocean area and its surroundings. Based on the pioneering studies by Bond et al. (1997, 2001) these events are called Bond Cycles and thought to be the Holocene equivalents of the Pleistocene Dansgaard-Oeschger cycles. The first event was the Younger Dryas (~12,000 BP; Broecker 2006), the last one was the Little Ice Age (AD 1350-1860; Grove 1988). A number of trigger mechanisms is discussed (see Table 1), but a theory for the Bond Cycles does not exist. Based on spectral analyses of both, forcing factors and climatological time series, we argue that one single process did likely not cause the Holocene cooling events. It is conceivable that the early Holocene coolings were triggered by meltwater pulses. However, the late Holocene events (e.g., the Little Ice Age) were rather caused by a combination of different trigger mechanisms. In every case it has to be taken in mind that natural variability was also playing a decisive role.' - 'passage: During the Holocene (last 12,000 years) nine cold relapses were observed mainly in the North Atlantic Ocean area and its surroundings. Based on the pioneering studies by Bond et al. (1997, 2001) these events are called Bond Cycles and thought to be the Holocene equivalents of the Pleistocene Dansgaard-Oeschger cycles. The first event was the Younger Dryas (~12,000 BP; Broecker 2006), the last one was the Little Ice Age (AD 1350-1860; Grove 1988). A number of trigger mechanisms is discussed (see Table 1), but a theory for the Bond Cycles does not exist. Based on spectral analyses of both, forcing factors and climatological time series, we argue that one single process did likely not cause the Holocene cooling events. It is conceivable that the early Holocene coolings were triggered by meltwater pulses. However, the late Holocene events (e.g., the Little Ice Age) were rather caused by a combination of different trigger mechanisms. In every case it has to be taken in mind that natural variability was also playing a decisive role.' - 'passage: A chronic difficulty in obtaining reliable climate records from satellites has been changes in instruments, platforms, equator-crossing times, and algorithms. The microwave sounding unit (MSU) tropospheric temperature record has overcome some of these problems, but evidence is presented that it too contains unreliable trends over a 17-yr period (1979–95) because of transitions involving different satellites and complications arising from nonatmospheric signals associated with the surface. The two primary MSU measures of tropospheric temperature contain different error characteristics and trends. The MSU channel 2 record exhibits a slight warming trend since 1979. Its broad vertical weighting function means that the temperature signal originates from throughout the troposphere and part of the lower stratosphere; intersatellite comparisons reveal low noise levels. Off-nadir channel 2 data are combined to provide an adjusted weighting function (called MSU 2R) without the stratospheric signal, but at a cost of an increased influence of surface emissions. Land surface microwave emissions, which account for about 20% of the total signal, depend on ground temperature and soil moisture and are subject to large variations associated with the diurnal cycle. The result is that MSU 2R noise levels are a factor of 3 larger than for MSU 2 and are sufficient to corrupt trends when several satellite records are merged. After allowing for physical differences between the satellite and surface records, large differences remain in temperature trends over the Tropics where there is a strong and deterministic coupling with the surface. The authors use linear regression with observed sea surface temperatures (SSTs) and an atmospheric general circulation model to relate the tropical MSU and surface datasets. These and alternative analyses of the MSU data, radiosonde data, and comparisons between the MSU 2R and channel 2 records, with estimates of their noise, are used to show that the downward trend in tropical MSU 2R temperatures is very likely spurious. Tropical radiosonde records are of limited use in resolving the discrepancies because of artificial trends arising from changes in instruments or sensors;however, comparisons with Australian radiosondes show a spurious downward jump in MSU 2R in mid-1991, which is not evident in MSU 2. Evaluation of reanalyzed tropical temperatures from the National Centers for Environmental Prediction and the European Centre for Medium-Range Weather Forecasts shows that they contain very different and false trends, as the analyses are only as good as the input database. Statistical analysis of the MSU 2R record objectively identifies two stepwise downward discontinuities that coincide with satellite transitions. The first is in mid-1981, prior to which only one satellite was in operation for much of the time so the diurnal cycle was not well sampled. Tropical SST anomalies over these years were small, in agreement with the Southern Oscillation index, yet the MSU 2R values were anomalously warm by ∌0.25°C. The second transition from NOAA-10 to NOAA-12 in mid-1991 did not involve an overlap except with NOAA-11, which suffered from a large drift in its equator-crossing times. MSU 2R anomalies have remained anomalously cold since mid-1991 by ∌0.1°C. Adding the two stepwise discontinuities to the tropical MSU 2R record allows it to be completely reconciled with the SST record within expected noise levels. The statistical results also make physical sense as the tropical satellite anomalies are magnified relative to SST anomalies by a factor of ∌1.3, which is the amplification expected following the saturated adiabatic lapse rate to the level of the peak weighting function of MSU 2R.' pipeline_tag: sentence-similarity library_name: sentence-transformers metrics: - cosine_accuracy co2_eq_emissions: emissions: 8.54717166082493 energy_consumed: 0.02243646583757692 source: codecarbon training_type: fine-tuning on_cloud: false cpu_model: AMD EPYC 9254 24-Core Processor ram_total_size: 1511.6277809143066 hours_used: 0.069 hardware_used: 1 x NVIDIA H100 PCIe model-index: - name: SentenceTransformer based on intfloat/e5-large-v2 results: - task: type: triplet name: Triplet dataset: name: claims abstracts dev type: claims-abstracts-dev metrics: - type: cosine_accuracy value: 0.9666666388511658 name: Cosine Accuracy --- # SentenceTransformer based on intfloat/e5-large-v2 This is a [sentence-transformers](https://www.SBERT.net) model finetuned from [intfloat/e5-large-v2](https://huggingface.co/intfloat/e5-large-v2). It maps sentences & paragraphs to a 1024-dimensional dense vector space and can be used for semantic textual similarity, semantic search, paraphrase mining, text classification, clustering, and more. ## Model Details ### Model Description - **Model Type:** Sentence Transformer - **Base model:** [intfloat/e5-large-v2](https://huggingface.co/intfloat/e5-large-v2) - **Maximum Sequence Length:** 512 tokens - **Output Dimensionality:** 1024 dimensions - **Similarity Function:** Cosine Similarity ### Model Sources - **Documentation:** [Sentence Transformers Documentation](https://sbert.net) - **Repository:** [Sentence Transformers on GitHub](https://github.com/huggingface/sentence-transformers) - **Hugging Face:** [Sentence Transformers on Hugging Face](https://huggingface.co/models?library=sentence-transformers) ### Full Model Architecture ``` SentenceTransformer( (0): Transformer({'max_seq_length': 512, 'do_lower_case': False, 'architecture': 'BertModel'}) (1): Pooling({'word_embedding_dimension': 1024, 'pooling_mode_cls_token': False, 'pooling_mode_mean_tokens': True, 'pooling_mode_max_tokens': False, 'pooling_mode_mean_sqrt_len_tokens': False, 'pooling_mode_weightedmean_tokens': False, 'pooling_mode_lasttoken': False, 'include_prompt': True}) (2): Normalize() ) ``` ## Usage ### Direct Usage (Sentence Transformers) First install the Sentence Transformers library: ```bash pip install -U sentence-transformers ``` Then you can load this model and run inference. ```python from sentence_transformers import SentenceTransformer # Download from the đŸ€— Hub model = SentenceTransformer("sentence_transformers_model_id") # Run inference sentences = [ "query: Apparently, the air a bit higher up isn't warming as much as the ground level, according to satellite data. đŸ€” #climate #science", 'passage: A chronic difficulty in obtaining reliable climate records from satellites has been changes in instruments, platforms, equator-crossing times, and algorithms. The microwave sounding unit (MSU) tropospheric temperature record has overcome some of these problems, but evidence is presented that it too contains unreliable trends over a 17-yr period (1979–95) because of transitions involving different satellites and complications arising from nonatmospheric signals associated with the surface. The two primary MSU measures of tropospheric temperature contain different error characteristics and trends. The MSU channel 2 record exhibits a slight warming trend since 1979. Its broad vertical weighting function means that the temperature signal originates from throughout the troposphere and part of the lower stratosphere; intersatellite comparisons reveal low noise levels. Off-nadir channel 2 data are combined to provide an adjusted weighting function (called MSU 2R) without the stratospheric signal, but at a cost of an increased influence of surface emissions. Land surface microwave emissions, which account for about 20% of the total signal, depend on ground temperature and soil moisture and are subject to large variations associated with the diurnal cycle. The result is that MSU 2R noise levels are a factor of 3 larger than for MSU 2 and are sufficient to corrupt trends when several satellite records are merged. After allowing for physical differences between the satellite and surface records, large differences remain in temperature trends over the Tropics where there is a strong and deterministic coupling with the surface. The authors use linear regression with observed sea surface temperatures (SSTs) and an atmospheric general circulation model to relate the tropical MSU and surface datasets. These and alternative analyses of the MSU data, radiosonde data, and comparisons between the MSU 2R and channel 2 records, with estimates of their noise, are used to show that the downward trend in tropical MSU 2R temperatures is very likely spurious. Tropical radiosonde records are of limited use in resolving the discrepancies because of artificial trends arising from changes in instruments or sensors;however, comparisons with Australian radiosondes show a spurious downward jump in MSU 2R in mid-1991, which is not evident in MSU 2. Evaluation of reanalyzed tropical temperatures from the National Centers for Environmental Prediction and the European Centre for Medium-Range Weather Forecasts shows that they contain very different and false trends, as the analyses are only as good as the input database. Statistical analysis of the MSU 2R record objectively identifies two stepwise downward discontinuities that coincide with satellite transitions. The first is in mid-1981, prior to which only one satellite was in operation for much of the time so the diurnal cycle was not well sampled. Tropical SST anomalies over these years were small, in agreement with the Southern Oscillation index, yet the MSU 2R values were anomalously warm by ∌0.25°C. The second transition from NOAA-10 to NOAA-12 in mid-1991 did not involve an overlap except with NOAA-11, which suffered from a large drift in its equator-crossing times. MSU 2R anomalies have remained anomalously cold since mid-1991 by ∌0.1°C. Adding the two stepwise discontinuities to the tropical MSU 2R record allows it to be completely reconciled with the SST record within expected noise levels. The statistical results also make physical sense as the tropical satellite anomalies are magnified relative to SST anomalies by a factor of ∌1.3, which is the amplification expected following the saturated adiabatic lapse rate to the level of the peak weighting function of MSU 2R.', 'passage: During the Holocene (last 12,000 years) nine cold relapses were observed mainly in the North Atlantic Ocean area and its surroundings. Based on the pioneering studies by Bond et al. (1997, 2001) these events are called Bond Cycles and thought to be the Holocene equivalents of the Pleistocene Dansgaard-Oeschger cycles. The first event was the Younger Dryas (~12,000 BP; Broecker 2006), the last one was the Little Ice Age (AD 1350-1860; Grove 1988). A number of trigger mechanisms is discussed (see Table 1), but a theory for the Bond Cycles does not exist. Based on spectral analyses of both, forcing factors and climatological time series, we argue that one single process did likely not cause the Holocene cooling events. It is conceivable that the early Holocene coolings were triggered by meltwater pulses. However, the late Holocene events (e.g., the Little Ice Age) were rather caused by a combination of different trigger mechanisms. In every case it has to be taken in mind that natural variability was also playing a decisive role.', ] embeddings = model.encode(sentences) print(embeddings.shape) # [3, 1024] # Get the similarity scores for the embeddings similarities = model.similarity(embeddings, embeddings) print(similarities) # tensor([[ 1.0000, 0.5938, -0.0103], # [ 0.5938, 1.0000, 0.0422], # [-0.0103, 0.0422, 1.0000]]) ``` ## Evaluation ### Metrics #### Triplet * Dataset: `claims-abstracts-dev` * Evaluated with [TripletEvaluator](https://sbert.net/docs/package_reference/sentence_transformer/evaluation.html#sentence_transformers.evaluation.TripletEvaluator) | Metric | Value | |:--------------------|:-----------| | **cosine_accuracy** | **0.9667** | ## Training Details ### Training Dataset #### Unnamed Dataset * Size: 2,993 training samples * Columns: anchor, positive, and negative * Approximate statistics based on the first 1000 samples: | | anchor | positive | negative | |:--------|:----------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------|:-----------------------------------| | type | string | string | list | | details | | | | * Samples: | anchor | positive | negative | |:-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------| | query: there is doubt that the survival of polar bears as a species is doomed | passage: Polar bears (Ursus maritimus) live throughout the ice-covered waters of the circumpolar Arctic, particularly in near shore annual ice over the continental shelf where biological productivity is highest. However, to a large degree under scenarios predicted by climate change models, these preferred sea ice habitats will be substantially altered. Spatial and temporal sea ice changes will lead to shifts in trophic interactions involving polar bears through reduced availability and abundance of their main prey: seals. In the short term, climatic warming may improve bear and seal habitats in higher latitudes over continental shelves if currently thick multiyear ice is replaced by annual ice with more leads, making it more suitable for seals. A cascade of impacts beginning with reduced sea ice will be manifested in reduced adipose stores leading to lowered reproductive rates because females will have less fat to invest in cubs during the winter fast. Non-pregnant bears may have to fa... | ['passage: Polar bears depend on sea ice for survival. Climate warming in the Arctic has caused significant declines in total cover and thickness of sea ice in the polar basin and progressively earlier breakup in some areas. Inuit hunters in the areas of four polar bear populations in the eastern Canadian Arctic (including Western Hudson Bay) have reported seeing more bears near settlements during the open-water period in recent years. In a fifth ecologically similar population, no changes have yet been reported by Inuit hunters. These observations, interpreted as evidence of increasing population size, have resulted in increases in hunting quotas. However, long-term data on the population size and body condition of polar bears in Western Hudson Bay, as well as population and harvest data from Baffin Bay, make it clear that those two populations at least are more likely to be declining, not increasing. While the ecological details vary in the regions occupied by the five different populations discussed in this paper, analysis of passive-microwave satellite imagery beginning in the late 1970s indicates that the sea ice is breaking up at progressively earlier dates, so that bears must fast for longer periods during the open-water season. Thus, at least part of the explanation for the appearance of more bears near coastal communities and hunting camps is likely that they are searching for alternative food sources in years when their stored body fat depots may be depleted before freeze-up, when they can return to the sea ice to hunt seals again. We hypothesize that, if the climate continues to warm as projected by the Intergovernmental Panel on Climate Change (IPCC), then polar bears in all five populations discussed in this paper will be increasingly food-stressed, and their numbers are likely to decline eventually, probably significantly so. As these populations decline, problem interactions between bears and humans will likely continue, and possibly increase, as the bears seek alternative food sources. Taken together, the data reported in this paper suggest that a precautionary approach be taken to the harvesting of polar bears and that the potential effects of climate warming be incorporated into planning for the management and conservation of this species throughout the Arctic.', 'passage: Loss of Arctic sea ice owing to climate change is the primary threat to polar bears throughout their range. We evaluated the potential response of polar bears to sea-ice declines by (i) calculating generation length (GL) for the species, which determines the timeframe for conservation assessments; (ii) developing a standardized sea-ice metric representing important habitat; and (iii) using statistical models and computer simulation to project changes in the global population under three approaches relating polar bear abundance to sea ice. Mean GL was 11.5 years. Ice-covered days declined in all subpopulation areas during 1979–2014 (median −1.26 days year −1 ). The estimated probabilities that reductions in the mean global population size of polar bears will be greater than 30%, 50% and 80% over three generations (35–41 years) were 0.71 (range 0.20–0.95), 0.07 (range 0–0.35) and less than 0.01 (range 0–0.02), respectively. According to IUCN Red List reduction thresholds, which provide a common measure of extinction risk across taxa, these results are consistent with listing the species as vulnerable. Our findings support the potential for large declines in polar bear numbers owing to sea-ice loss, and highlight near-term uncertainty in statistical projections as well as the sensitivity of projections to different plausible assumptions.', 'passage: Loss of Arctic sea ice owing to climate change is the primary threat to polar bears throughout their range. We evaluated the potential response of polar bears to sea-ice declines by (i) calculating generation length (GL) for the species, which determines the timeframe for conservation assessments; (ii) developing a standardized sea-ice metric representing important habitat; and (iii) using statistical models and computer simulation to project changes in the global population under three approaches relating polar bear abundance to sea ice. Mean GL was 11.5 years. Ice-covered days declined in all subpopulation areas during 1979–2014 (median −1.26 days year −1 ). The estimated probabilities that reductions in the mean global population size of polar bears will be greater than 30%, 50% and 80% over three generations (35–41 years) were 0.71 (range 0.20–0.95), 0.07 (range 0–0.35) and less than 0.01 (range 0–0.02), respectively. According to IUCN Red List reduction thresholds, which provide a common measure of extinction risk across taxa, these results are consistent with listing the species as vulnerable. Our findings support the potential for large declines in polar bear numbers owing to sea-ice loss, and highlight near-term uncertainty in statistical projections as well as the sensitivity of projections to different plausible assumptions.'] | | query: Other factors than CO2 like water vapor play a bigger role in determining the Earth's climate. | passage: Carbon dioxide (CO2) and methane (CH4) are important greenhouse gases in the atmosphere and have large impacts on Earth's radiative forcing and climate. Their natural and anthropogenic emissions have often been in focus, while the role of human metabolic emissions has received less attention. In this study, exhaled, dermal and whole-body CO2 and CH4 emission rates from a total of 20 volunteers were quantified under various controlled environmental conditions in a climate chamber. The whole-body CO2 emissions increased with temperature. Individual differences were the most important factor for the whole-body CH4 emissions. Dermal emissions of CO2 and CH4 only contributed ~3.5% and ~5.5% to the whole-body emissions, respectively. Breath measurements conducted on 24 volunteers in a companion study identified one third of the volunteers as CH4 producers (exhaled CH4 exceeded 1 ppm above ambient level). The exhaled CH4 emission rate of these CH4 producers (4.03 ± 0.71 mg/h/person, ... | ['passage: Significance The fact that water vapor is the most dominant greenhouse gas underscores the need for an accurate understanding of the changes in its distribution over space and time. Although satellite observations have revealed a moistening trend in the upper troposphere, it has been unclear whether the observed moistening is a facet of natural variability or a direct result of human activities. Here, we use a set of coordinated model experiments to confirm that the satellite-observed increase in upper-tropospheric water vapor over the last three decades is primarily attributable to human activities. This attribution has significant implications for climate sciences because it corroborates the presence of the largest positive feedback in the climate system.', 'passage: Significance The fact that water vapor is the most dominant greenhouse gas underscores the need for an accurate understanding of the changes in its distribution over space and time. Although satellite observations have revealed a moistening trend in the upper troposphere, it has been unclear whether the observed moistening is a facet of natural variability or a direct result of human activities. Here, we use a set of coordinated model experiments to confirm that the satellite-observed increase in upper-tropospheric water vapor over the last three decades is primarily attributable to human activities. This attribution has significant implications for climate sciences because it corroborates the presence of the largest positive feedback in the climate system.', 'passage: Significance The fact that water vapor is the most dominant greenhouse gas underscores the need for an accurate understanding of the changes in its distribution over space and time. Although satellite observations have revealed a moistening trend in the upper troposphere, it has been unclear whether the observed moistening is a facet of natural variability or a direct result of human activities. Here, we use a set of coordinated model experiments to confirm that the satellite-observed increase in upper-tropospheric water vapor over the last three decades is primarily attributable to human activities. This attribution has significant implications for climate sciences because it corroborates the presence of the largest positive feedback in the climate system.'] | | query: Climate change is a long-term process. Even if it's entirely human-caused, it's happening so slowly that we won't see its full effects in our lifetime. That's why action is needed NOW. | passage: ‘Global warming’ may be a familiar term, but it is seriously misleading. Human actions are causing a massive disruption to the planet's climate that is severe, rapid, very variable over space and time, and highly complex. The biosphere itself is complex and its responses to even simple changes are difficult to predict in detail. One can likely only be certain that many changes will be unexpected and some unfortunate. Even the simple, slow warming of the climate will produce complex consequences to species numbers and distributions because of how species depend on each other. An alternative approach to worrying about details is to concentrate on understanding the most significant ecological changes, ones that are irreversible — so-called ‘tipping points’. Once such a point has been passed, even if society managed to restore historical climatic conditions, it might not restore the historical ecological patterns. Nowhere is this more obvious than in the loss of species, for we ca... | ["passage: ‘Global warming’ may be a familiar term, but it is seriously misleading. Human actions are causing a massive disruption to the planet's climate that is severe, rapid, very variable over space and time, and highly complex. The biosphere itself is complex and its responses to even simple changes are difficult to predict in detail. One can likely only be certain that many changes will be unexpected and some unfortunate. Even the simple, slow warming of the climate will produce complex consequences to species numbers and distributions because of how species depend on each other. An alternative approach to worrying about details is to concentrate on understanding the most significant ecological changes, ones that are irreversible — so-called ‘tipping points’. Once such a point has been passed, even if society managed to restore historical climatic conditions, it might not restore the historical ecological patterns. Nowhere is this more obvious than in the loss of species, for we cannot recreate them. Climate disruptions may cause the loss of a large fraction of the planet's biodiversity, even if the only mechanism were to be species ranges moving uphill as temperatures rise. ‘Global warming’ may be a familiar term, but it is seriously misleading. Human actions are causing a massive disruption to the planet's climate that is severe, rapid, very variable over space and time, and highly complex. The biosphere itself is complex and its responses to even simple changes are difficult to predict in detail. One can likely only be certain that many changes will be unexpected and some unfortunate. Even the simple, slow warming of the climate will produce complex consequences to species numbers and distributions because of how species depend on each other. An alternative approach to worrying about details is to concentrate on understanding the most significant ecological changes, ones that are irreversible — so-called ‘tipping points’. Once such a point has been passed, even if society managed to restore historical climatic conditions, it might not restore the historical ecological patterns. Nowhere is this more obvious than in the loss of species, for we cannot recreate them. Climate disruptions may cause the loss of a large fraction of the planet's biodiversity, even if the only mechanism were to be species ranges moving uphill as temperatures rise.", 'passage: Climate is changing in an accelerating pace. Climate change occurs as a result of an imbalance between incoming and outgoing radiation in the atmosphere. The global mean temperatures may increase up to 5.4°C by 2100. Climate change is mainly caused by humans, especially through increased greenhouse gas emissions. Climate change is recognized as a serious threat to ecosystem, biodiversity, and health. It is associated with alterations in the physical environment of the planet Earth. Climate change affects life around the globe. It impacts plants and animals, with consequences for the survival of the species. In humans, climate change has multiple deleterious consequences. Climate change creates water and food insecurity, increased morbidity/mortality, and population movement. Vulnerable populations (e.g., children, elderly, indigenous, and poor) are disproportionately affected. Personalized adaptation to the consequences of climate change and preventive measures are key challenges for the society. Policymakers must implement the appropriate strategies, especially in the vulnerable populations.', 'passage: Climate is changing in an accelerating pace. Climate change occurs as a result of an imbalance between incoming and outgoing radiation in the atmosphere. The global mean temperatures may increase up to 5.4°C by 2100. Climate change is mainly caused by humans, especially through increased greenhouse gas emissions. Climate change is recognized as a serious threat to ecosystem, biodiversity, and health. It is associated with alterations in the physical environment of the planet Earth. Climate change affects life around the globe. It impacts plants and animals, with consequences for the survival of the species. In humans, climate change has multiple deleterious consequences. Climate change creates water and food insecurity, increased morbidity/mortality, and population movement. Vulnerable populations (e.g., children, elderly, indigenous, and poor) are disproportionately affected. Personalized adaptation to the consequences of climate change and preventive measures are key challenges for the society. Policymakers must implement the appropriate strategies, especially in the vulnerable populations.'] | * Loss: [MultipleNegativesRankingLoss](https://sbert.net/docs/package_reference/sentence_transformer/losses.html#multiplenegativesrankingloss) with these parameters: ```json { "scale": 20.0, "similarity_fct": "cos_sim", "gather_across_devices": false } ``` ### Evaluation Dataset #### Unnamed Dataset * Size: 30 evaluation samples * Columns: anchor, positive, and negative * Approximate statistics based on the first 30 samples: | | anchor | positive | negative | |:--------|:----------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------|:--------------------------------------------------------------------------------------| | type | string | string | string | | details | | | | * Samples: | anchor | positive | negative | |:---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------| | query: While CO2 gets a lot of attention, it's actually water vapor that plays the biggest role in trapping heat in our atmosphere #ClimateAction #ClimateAwareness | passage: Carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O) are the greenhouse gases largely responsible for anthropogenic climate change. Natural plant and microbial metabolic processes play a major role in the global atmospheric budget of each. We have been studying ecosystem-atmosphere trace gas exchange at a sub-boreal forest in the northeastern United States for over two decades. Historically our emphasis was on turbulent fluxes of CO2 and water vapor. In 2012 we embarked on an expanded campaign to also measure CH4 and N2O. Here we present continuous tower-based measurements of the ecosystem-atmosphere exchange of CO2 and CH4, recorded over the period 2012-2018 and reported at a 30-minute time step. Additionally, we describe a five-year (2012-2016) dataset of chamber-based measurements of soil fluxes of CO2, CH4, and N2O (2013-2016 only), conducted each year from May to November. These data can be used for process studies, for biogeochemical and land surface model valida... | passage: Summary


1. Facilitating adaptive responses of organisms in modified landscape will be essential to overcome the negative effects of climate change and its interaction with land use change. Without such action, many organisms will be prevented from achieving the predicted range shifts they need to survive.



2. Scattered trees are a prominent feature of many modified landscapes, and could play an important role in facilitating climate change adaptation. They are keystone structures because of the disproportionally large ecological values and ecosystem services that they provide relative to the area they occupy in these landscapes. The provision of habitat and connectivity will be particularly relevant.



3. Scattered trees are declining in modified landscapes due to elevated tree mortality and poor recruitment often associated with intensive land use. The continuing global decline of scattered trees will undermine the capacity of many organisms to adapt to climat... | | query: The wealthy create disproportionately large carbon footprints. | passage: Shrinking household size is a key challenge for sustainability, simultaneously decreasing sharing and increasing resource consumption. We use the Danish Household Budget Survey and carbon intensities from EXIOBASE to characterise small households in socio-demographic cohorts along the carbon footprint spectrum. Single and dual occupant households represent 77% of the Danish carbon footprint and 73% of the sample, making these households highly relevant for climate and social policy. We identify high carbon footprint cohorts to determine potential intervention targets such as wealthy males living alone and couples in suburban areas. To add emotional depth to these characteristics we provide three stories to our results. Illuminating characteristics of high impact households provides a foundation from which to design and implement interventions to reduce the carbon consequences of the growing trend towards living alone. We also characterise low carbon footprint cohorts, with spe... | passage: We modelled the financial and environmental costs of two commonly used anaesthetic plastic drug trays. We proposed that, compared with single-use trays, reusable trays are less expensive, consume less water and produce less carbon dioxide, and that routinely adding cotton and paper increases financial and environmental costs. We used life cycle assessment to model the financial and environmental costs of reusable and single-use trays. From our life cycle assessment modelling, the reusable tray cost (Australian dollars) $0.23 (95% confidence interval [CI] $0.21 to $0.25) while the single-use tray alone cost $0.47 (price range of $0.42 to $0.52) and the single-use tray with cotton and gauze added was $0.90 (no price range in Melbourne). Production of CO2 was 110 g CO2 (95% CI 98 to 122 g CO2) for the reusable tray, 126 g (95% CI 104 to 151 g) for single-use trays alone (mean difference of 16 g, 95% CI -8 to 40 g) and 204 g CO2 (95% CI 166 to 268 g CO2) for the single-use trays w... | | query: Turns out, sea levels haven't been rising any faster in the last 120 years. #ClimateAction #Sustainability | passage: Abstract. Alteration of natural environment in the wake of global warming is one of the most serious issues, which is being discussed across the world. Over the last 100 years, global sea level rose by 1.0–2.5 mm/y. Present estimates of future sea-level rise induced by climate change range from 28 to 98 cm for the year 2100. It has been estimated that a 1-m rise in sea-level could displace nearly 7 million people from their homes in India. The climate change and associated sea level rise is proclaimed to be a serious threat especially to the low lying coastal areas. Thus, study of long term effects on an estuarine region not only gives opportunity for identifying the vulnerable areas but also gives a clue to the periods where the sea level rise was significant and verifies climate change impact on sea level rise. Multi-temporal remote sensing data and GIS tools are often used to study the pattern of erosion/ accretion in an area and to predict the future coast lines. The prese... | passage: The 2015 Paris Agreement on Climate Change implicitly requires phasing out fossil fuels; such a phase out may cost hundreds of trillions of dollars and induce widespread socio-ecological ramifications. The COVID-19 'pancession' (pandemic + recession) has rattled global economies, possibly accelerating the fossil fuel phase out. This raises the question: What opportunities has COVID-19 presented to phase out fossil fuels, and subsequently, how can transformative recovery efforts be designed to utilize these opportunities and promote social, ecological and relational inclusiveness? We find that: (a) the COVID-19 pancession provides a unique opportunity to accelerate climate action, as it has devalued financial assets, stunned fossil fuel production and paralyzed relevant infrastructure, thus easing the pathway towards stranding global fossil fuel resources and assets; (b) four possible post-pancession recovery scenarios may unravel, of which only one is ecologically, socially an... | * Loss: [MultipleNegativesRankingLoss](https://sbert.net/docs/package_reference/sentence_transformer/losses.html#multiplenegativesrankingloss) with these parameters: ```json { "scale": 20.0, "similarity_fct": "cos_sim", "gather_across_devices": false } ``` ### Training Hyperparameters #### Non-Default Hyperparameters - `eval_strategy`: epoch - `per_device_train_batch_size`: 16 - `per_device_eval_batch_size`: 16 - `learning_rate`: 2e-05 - `warmup_ratio`: 0.1 - `fp16`: True - `load_best_model_at_end`: True - `batch_sampler`: no_duplicates #### All Hyperparameters
Click to expand - `overwrite_output_dir`: False - `do_predict`: False - `eval_strategy`: epoch - `prediction_loss_only`: True - `per_device_train_batch_size`: 16 - `per_device_eval_batch_size`: 16 - `per_gpu_train_batch_size`: None - `per_gpu_eval_batch_size`: None - `gradient_accumulation_steps`: 1 - `eval_accumulation_steps`: None - `torch_empty_cache_steps`: None - `learning_rate`: 2e-05 - `weight_decay`: 0.0 - `adam_beta1`: 0.9 - `adam_beta2`: 0.999 - `adam_epsilon`: 1e-08 - `max_grad_norm`: 1.0 - `num_train_epochs`: 3 - `max_steps`: -1 - `lr_scheduler_type`: linear - `lr_scheduler_kwargs`: {} - `warmup_ratio`: 0.1 - `warmup_steps`: 0 - `log_level`: passive - `log_level_replica`: warning - `log_on_each_node`: True - `logging_nan_inf_filter`: True - `save_safetensors`: True - `save_on_each_node`: False - `save_only_model`: False - `restore_callback_states_from_checkpoint`: False - `no_cuda`: False - `use_cpu`: False - `use_mps_device`: False - `seed`: 42 - `data_seed`: None - `jit_mode_eval`: False - `bf16`: False - `fp16`: True - `fp16_opt_level`: O1 - `half_precision_backend`: auto - `bf16_full_eval`: False - `fp16_full_eval`: False - `tf32`: None - `local_rank`: 0 - `ddp_backend`: None - `tpu_num_cores`: None - `tpu_metrics_debug`: False - `debug`: [] - `dataloader_drop_last`: False - `dataloader_num_workers`: 0 - `dataloader_prefetch_factor`: None - `past_index`: -1 - `disable_tqdm`: False - `remove_unused_columns`: True - `label_names`: None - `load_best_model_at_end`: True - `ignore_data_skip`: False - `fsdp`: [] - `fsdp_min_num_params`: 0 - `fsdp_config`: {'min_num_params': 0, 'xla': False, 'xla_fsdp_v2': False, 'xla_fsdp_grad_ckpt': False} - `fsdp_transformer_layer_cls_to_wrap`: None - `accelerator_config`: {'split_batches': False, 'dispatch_batches': None, 'even_batches': True, 'use_seedable_sampler': True, 'non_blocking': False, 'gradient_accumulation_kwargs': None} - `parallelism_config`: None - `deepspeed`: None - `label_smoothing_factor`: 0.0 - `optim`: adamw_torch_fused - `optim_args`: None - `adafactor`: False - `group_by_length`: False - `length_column_name`: length - `project`: huggingface - `trackio_space_id`: trackio - `ddp_find_unused_parameters`: None - `ddp_bucket_cap_mb`: None - `ddp_broadcast_buffers`: False - `dataloader_pin_memory`: True - `dataloader_persistent_workers`: False - `skip_memory_metrics`: True - `use_legacy_prediction_loop`: False - `push_to_hub`: False - `resume_from_checkpoint`: None - `hub_model_id`: None - `hub_strategy`: every_save - `hub_private_repo`: None - `hub_always_push`: False - `hub_revision`: None - `gradient_checkpointing`: False - `gradient_checkpointing_kwargs`: None - `include_inputs_for_metrics`: False - `include_for_metrics`: [] - `eval_do_concat_batches`: True - `fp16_backend`: auto - `push_to_hub_model_id`: None - `push_to_hub_organization`: None - `mp_parameters`: - `auto_find_batch_size`: False - `full_determinism`: False - `torchdynamo`: None - `ray_scope`: last - `ddp_timeout`: 1800 - `torch_compile`: False - `torch_compile_backend`: None - `torch_compile_mode`: None - `include_tokens_per_second`: False - `include_num_input_tokens_seen`: no - `neftune_noise_alpha`: None - `optim_target_modules`: None - `batch_eval_metrics`: False - `eval_on_start`: False - `use_liger_kernel`: False - `liger_kernel_config`: None - `eval_use_gather_object`: False - `average_tokens_across_devices`: True - `prompts`: None - `batch_sampler`: no_duplicates - `multi_dataset_batch_sampler`: proportional - `router_mapping`: {} - `learning_rate_mapping`: {}
### Training Logs | Epoch | Step | Training Loss | Validation Loss | claims-abstracts-dev_cosine_accuracy | |:-------:|:-------:|:-------------:|:---------------:|:------------------------------------:| | -1 | -1 | - | - | 0.9333 | | 0.5319 | 100 | 1.1308 | - | - | | 1.0 | 188 | - | 0.2670 | 0.9667 | | 1.0638 | 200 | 0.3978 | - | - | | 1.5957 | 300 | 0.2429 | - | - | | 2.0 | 376 | - | 0.1914 | 0.9667 | | 2.1277 | 400 | 0.2063 | - | - | | 2.6596 | 500 | 0.1328 | - | - | | **3.0** | **564** | **-** | **0.1797** | **0.9667** | * The bold row denotes the saved checkpoint. ### Environmental Impact Carbon emissions were measured using [CodeCarbon](https://github.com/mlco2/codecarbon). - **Energy Consumed**: 0.022 kWh - **Carbon Emitted**: 0.009 kg of CO2 - **Hours Used**: 0.069 hours ### Training Hardware - **On Cloud**: No - **GPU Model**: 1 x NVIDIA H100 PCIe - **CPU Model**: AMD EPYC 9254 24-Core Processor - **RAM Size**: 1511.63 GB ### Framework Versions - Python: 3.12.7 - Sentence Transformers: 5.1.2 - Transformers: 4.57.1 - PyTorch: 2.9.0+cu128 - Accelerate: 1.10.1 - Datasets: 4.2.0 - Tokenizers: 0.22.1 ## Citation ### BibTeX #### Sentence Transformers ```bibtex @inproceedings{reimers-2019-sentence-bert, title = "Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks", author = "Reimers, Nils and Gurevych, Iryna", booktitle = "Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing", month = "11", year = "2019", publisher = "Association for Computational Linguistics", url = "https://arxiv.org/abs/1908.10084", } ``` #### MultipleNegativesRankingLoss ```bibtex @misc{henderson2017efficient, title={Efficient Natural Language Response Suggestion for Smart Reply}, author={Matthew Henderson and Rami Al-Rfou and Brian Strope and Yun-hsuan Sung and Laszlo Lukacs and Ruiqi Guo and Sanjiv Kumar and Balint Miklos and Ray Kurzweil}, year={2017}, eprint={1705.00652}, archivePrefix={arXiv}, primaryClass={cs.CL} } ```