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Left-Out Left
Left-Out Left are a Democratic-oriented group marked by low expectations of the political system and a feeling that they are not well-represented. They largely doubt that political action will meaningfully improve their lives. And while they like the Democratic Party considerably more than the Republican Party, their evaluations of Democrats are lukewarm at best. Left-Out […]
Order and Opportunity Left
Order and Opportunity Left are the largest group in the political typology, making up 18% of the American public. They generally support a larger federal government with more services and are critical of some aspects of the economic system. But they couple this with a greater sense of economic individualism than the typology groups more […]
Tuned-Out Middle
Tuned-Out Middle are defined largely by their relatively low levels of interest in politics and participation in elections. While they are roughly equally likely to associate with the Republican and Democratic parties, most don’t identify as partisans, and they tend not to hold strong positions on political issues. Just 32% voted in the 2024 election. […]
Pragmatic and Polite Right
Pragmatic and Polite Right hold a mix of conservative, moderate and somewhat liberal issue positions: They skew more conservative on economics and the role of government, while tilting more liberal on issues related to race and in their orientation to the rest of the world. They are also moderate in their style, prizing civility and […]
Unconventional Right
Unconventional Right are a Republican-oriented group with conservative values in many areas – but not across the board. Largely supportive of restrictions on immigration and concerned about its impact on the country, they are also skeptical of efforts to promote diversity in workplaces and schools. Unconventional Right are one of nine groups in Pew Research […]
Faith First Conservatives
Faith First Conservatives are deeply conservative in their political values and are stalwart supporters of the Republican Party and Donald Trump, though their political style is not as uncompromising as No Apologies Right (the other typology group firmly at the core of the Republican coalition). They are highly religious and hold traditional stances on many […]
No Apologies Right
No Apologies Right are overwhelmingly supportive of President Donald Trump’s agenda and the Make America Great Again movement. They take very conservative stances across a wide range of issues, and nearly all identify as Republicans or lean toward the party. No Apologies Right view the United States as standing above all other countries and are […]
Beyond Red vs. Blue: The Political Typology
Our typology sorts the public into nine groups based on their political and cultural values, not their party – painting a picture of American politics with far more than two colors.
Study splits Americans into nine political groups. Where do you belong?
Polling 10,000 Americans, the Pew Research Center found divisions on the political left and right, plus the Tuned-Out Middle.
Scientists May Have Pinpointed Physical Evidence of Our Consciousness
New research on brainwaves in the thalamus shows patterns distinctly linked to conscious states.
How AI Will Change the Job Market—and Boost These Health Insurance Stocks
Barclays upgraded its rating of Oscar to overweight, a buy equivalent, and reiterated its overweight rating on Centene in a new research note.
How to tell if your dog is left-pawed or right-pawed, according to science
A step-by-step guide to the “Doginburgh Inventory,” a new pawedness test developed by dog behavior researchers
Ecosystems have an afterlife, where dead help shape the living, research finds
New study reveals the physical remains of plants and animals that shape entire ecosystems continue to influence the environment long after death.
How science is securing Michigan's pork future
Seventy-five percent of state's pigs are now covered by an SPS on-farm biosecurity plan, strengthening the responses farmers will have to an FAD.
Biochemistry Student to Participate in National Science Foundation Undergraduate Research Program
Elmhurst University biochemistry major Hannah Cardenas ’27, of Des Plaines, Illinois, received a National Science Foundation Research Experiences for Undergraduates (NSF REU) award to participate in a 10-week summer research internship at the University of Texas at Dallas.
Emory gets $15M NIH grant to research Superfund sites’ health effects
Emory University has been awarded a five-year, $15 million grant from the NIH to study the link between environmental contaminants and human health in Brunswick, Georgia, which is home to four of the state's 23 Superfund sites.
Biobehavioral health researcher earns Lloyd Prize for Innovative Health Research
Penn State’s Social Science Research Institute has announced Mohanraj Krishnan as the recipient of the 2026 Lloyd Prize for Innovative Health Research made possible by an endowment created by Penn State Professor Emeritus Thomas Lloyd, who served on the College of Medicine faculty for 46 years.
National Science Foundation cuts mean researchers like me are losing grants – but impacts extend far beyond academia
As the National Science Foundation starts giving out fewer grants, people worldwide will potentially lose out from potential research findings that could help improve their lives.
Cell Therapy Clinical Trials: Breaking Down the Science
Breakthrough T1D is here to answer all of your questions about islet cell therapies, from the research lab to real-world treatments.
What Brands Get Wrong About Sports Sponsorships—and How to Get Them Right
Companies spend billions sponsoring major sporting events, yet many still evaluate success primarily through exposure metrics such as logo visibility and immediate brand recall. New research suggests those measures increasingly misrepresent sponsorship effectiveness because consumers form long-lasting, overlapping associations among brands, events, and competitors within crowded sponsorship ecosystems. Brands generate more enduring value when they focus less on visibility and more on authentic participation, distinctive experiences, and emotional engagement that strengthen trust and meaningful long-term recall.
SAVE THE DATE: COSPAR 2026 – The World’s largest Space Science Assembly heads to Florence (1-9 August 2026)
Registration is now officially open for media representatives, bloggers, and freelance communicators to attend the 46th COSPAR Scientific Assembly in August 2026. The event will gather over 3,000 global experts to unveil and discuss the latest groundbreaking discoveries shaping the future of space research
Scientists, higher ed alarmed by federal 'power grab' over research funding
The Trump administration has proposed regulations to control billions of dollars in federal research funding, which it says will reduce "fraud and abuse." Scientists in Massachusetts and beyond say they could set back research in the U.S. by decades.
New OMB rule could break science in the United States
The drug that saved your mother. The treatment your doctor recommended. The clinical trial that bought someone you love more time. None of it was inevitable. It required a system built to operate outside politics and sustained over decades, because science doesn’t operate on the timeline of a politician. That system is now under direct threat. The Office of Management and Budget (OMB) has proposed a new rule to regulate all federal grants, not just science, but housing, education, defense, NASA and everything in between, that would fundamentally change how research is conducted in the United States. There have been a lot of fires in the past 16 months, and if everything is an emergency, nothing is an emergency. But this is a very big deal. These rules would strip away the independence that has kept science from becoming a political tool. The good news is there’s still something we can all do. How the grant system was designed to work When I was a new faculty member, I was full of millions of ideas, so I sat down and wrote an NIH proposal. I worked on it for months and thought it was so good. Then I sent it to my mentor. It came back covered in comments. Places where my reasoning wasn’t as airtight as I’d thought, methods that could be stronger, gaps in my thinking that I had been too close to the work to see. It stung, as honest feedback always does, but peer review almost always makes the work better. In fact, it’s the backbone of how American science has functioned for generations. At NIH, submitted proposals go to a panel of scientists who have experience in the field. These are the people who can read research methods and spot their weaknesses, who understand when an experiment is designed well and when it isn’t. Applications are scored rigorously, and often only the top 3-20% of proposals receive funding. The people making funding decisions are required to justify them based on these reviews. To be clear: this is not a perfect system, and good science still goes unfunded more often than any of us would like due to limited resources. There is also criticism that peer review may undervalue bold ideas that are risky but could have high payoffs. But the peer review system is nonetheless a meaningful part of the grant selection process. While thoughtful and careful changes could improve the system, the changes being proposed by OMB will not make things better. The rule that could change everything Through this OMB proposal, the system that helps decide what gets funded is being dismantled. There are many troubling elements buried in this proposal, but three provisions stand out in particular. Each would be damaging alone. Together, they would change what kind of science gets done in America, and who it serves. 1. Political appointees would decide which science gets funded, and peer review would be explicitly sidelined or ignored. The guidelines your doctor follows, the standards that determine what’s in your air and water, the drugs that get approved for your family: all of it starts with a funding decision. Right now, that decision is made by scientists who can evaluate whether the work is actually sound and whether it could move the needle forward. Under this proposal, funding decisions could be made by political appointees. The careful, expertise-driven review process that shapes grant funding would be effectively sidelined. That means that a poorly designed study could get funded simply because someone in a political office liked the sound of it, while rigorous, important work doesn’t get funded because it no longer aligns with the administration’s priorities. In other words, critical work that benefits all of us could now be missed just because it has become politically inconvenient. 2. Grants could be canceled at any point, without warning, in the middle of ongoing work. Say your tax dollars have been paying for a cancer study for two years. The grant was awarded for five years, so the team is mid-experiment. There are three additional years’ worth of answers that could change how the disease is treated for hundreds of thousands of people. With this new rule, the federal government could cancel the remaining funding tomorrow, walk away from the commitment it made with your money, and have no legal obligation to finish what it started. This is a huge waste of money. There are rarely other sources of funding for this work, which means the team, the graduate students, postdocs, and research staff who have dedicated years of their careers to this project could lose their jobs. Patients who have contributed their time to studies may not see it turn into useful learnings for others. Every hour of work already completed could result in nothing useful. Science can take decades to get to tangible outcomes. It needs a stable funding system to flourish. 3. Researchers would have a harder time communicating their findings without pre-approval from the federal government. There is a saying from Sir Mark Walport: “Science isn’t finished until it’s communicated.” Science is no use to anyone if it is kept locked away in the labs that produced the data. The proposed rule could make communicating research findings harder in a number of ways: Make it harder for scientists to widely share their findings in scientific journals. Publication costs, including journal fees that allow for broad public access, could not be paid for by federal funds which is often how scientists pay these costs. Restrict researchers from engaging publicly about how their findings should inform policy or public health guidelines. This would restrict scientists from doing the work that transforms years of lab work into decisions that actually affect people’s lives. Make it harder for scientists to attend conferences. Conferences would now need to be approved by the federal agency at the time of grant award. This disadvantages conferences or publications that are not politically aligned. Conferences are a key way in which scientists learn about work happening in their field so they can collaborate and build on each other’s findings. What good is science with a muzzle? The long-term impact These changes could (and hopefully would) be reversed under the next administration. But by then, damage has been done. Once projects are halted or denied funding by political appointees, people leave their science careers for other paths or even leave the country to do their amazing science elsewhere. You cannot pause a scientific study the way you pause a subscription you decided isn’t useful anymore. You cannot freeze a research team that depends on salaries to feed their families, causing a scramble for replacement funding that, in most cases, simply does not exist. When the money stops, everything stops, and all the work in progress and its potential are lost. Despite all of the language about reducing waste, fraud, and abuse, this new proposed rule increases the administrative burden tremendously. Every researcher watching this unfold will make a rational decision: don’t start anything that will take a decade to finish. This includes not building a team around funding that could vanish, or asking the big questions that need patience and stability to answer. The most consequential science, the kind that produces the treatments and the breakthroughs that reach your doctor’s office twenty years from now, is exactly the science that would be abandoned first. This is still a proposal, so we can all do something Some worry this rule is already a done deal. But by law, OMB is required to open a public comment period. Those comments matter because they inform members of Congress, they can be used in litigation, and they create a public record. So here’s what you can do: Submit a public comment. The public comment period on this proposed change is open until July 13. Anyone can submit a comment, and OMB is required to respond to substantial ones. Each comment must be different to count as distinct; identical comments will be counted only once. Comment as an individual, not on behalf of your organization. Here’s a full resource to help you, with useful examples, but in general: Share a story about how science or federal funding has benefitted you or is involved in your work. Are you or someone you loved a cancer survivor? Do you know someone with Alzheimer’s? Have you received NIH/NSF or other federal funding? All of these can be stories you use to highlight why you care. Explain why you’re worried about these proposed changes. You can use the wording found here or in other resources to help you. Ask them to withdraw this proposed rule. Contact your elected representatives. Congress allocates money to federal agencies to spend, and it has oversight of how that process works. You can let your representatives know this proposed change concerns you and ask them to intervene. There are levers they can push that can help at this moment. Let others know why federal funding matters. This isn’t just about science, but ALL federal grants, including for education systems, defense projects, and more. The process, including the importance of federal funding, is invisible to many. We can all make it more visible by sharing how science benefits us and why we value it. You can also share this article, or any of the resources linked here, to help spread awareness! Bottom line We are quickly losing ground in scientific research in the U.S. More changes, like the proposed rule by OMB, would decimate our ability to conduct research here, leaving us all worse off: fewer treatments for pancreatic cancer, less research on pollution impacts, fewer answers for patients with rare disease, and more unaddressed health needs. The impact will be very real for all of us, regardless of where we stand politically. Using our voices for science is more important than ever. Love, LM Big thanks to Dr. Megan Ranney for reading this over and providing brilliant insights, as always. Dr. Liz Marnik, PhD, is Executive Director of The Evidence Collective at YLE and a science communicator and immunologist working at the intersection of public trust, science, and public health. You can find her on Substack, LinkedIn, Instagram and Threads. Your Local Epidemiologist (YLE) comprises a team of experts, ranging from physicians to immunologists to epidemiologists to nutritionists, working together with one goal: to “Translate” ever-evolving public health science so that people are well-equipped to make evidence-based decisions. The YLE suite of newsletters reaches over 475,000 people across more than 132 countries. This newsletter is free to everyone, thanks to the generous support of fellow YLE community members. To support the effort, subscribe or upgrade below: Subscribe
Meet the Researcher: Jianbin Ruan, UConn Health
Jianbin Ruan's lab studies how our immune system works at the molecular level, paving the way for better treatments
Could £400m research park plan make Norwich a global science hub?
Experts hope a revamp at the Norwich Research Park could lead to more scientific breakthroughs.
UMass Chan research finds Medicaid-funded nutrition, housing programs linked to improved health outcomes, lower costs
New research finds Medicaid-funded nutrition and housing programs are linked to improved health outcomes and lower healthcare costs in Massachusetts.
Ferris seniors place second in world in environmental science competition for research on smoke and agriculture
Sitting at the awards ceremony for the largest international high school science fair in the world this May, Ferris High School students Teddy Osborne and Anders Thogerson were a bit disappointed as the judge read off the fourth-place winners for projects in environmental science.
Researchers are furious over Anthropic's hidden AI limits
Anthropic faces backlash as Mythos-based models intentionally limit help for AI research, raising transparency and ethical concerns.
Outgoing US National Academy of Sciences head warns of ‘turmoil’ ...
NAS president addresses research funding worries, the need to revamp the promotion and tenure system and how AI can help
Science for kids: a melody that mends
Pediatric Research - Science for kids: a melody that mends
A classic brain test exposed AI's biggest weakness
Researchers gave top AI models a classic attention test used in psychology and found a major flaw. While the models could correctly name colors in short lists, their performance deteriorated sharply as the task became longer and more complex. Some leading systems fell from over 90% accuracy to nearly complete failure.
Popular joint supplement glucosamine linked to faster Alzheimer’s progression
A major study suggests glucosamine, a popular supplement for joint pain, could be linked to faster progression from mild cognitive impairment to Alzheimer’s disease. Researchers found a 25% higher likelihood of developing dementia among glucosamine users and uncovered biological clues that may explain why.
Federal science agencies facing a ‘generational loss,’ nonprofit says
New research from the Partnership for Public Service finds that many science agencies were cut deeply in the Trump administration’s workforce overhauls.
The science of seeing inside explosions
During the Manhattan Project, Los Alamos scientists needed a diagnostic tool. Like an x-ray confirming a broken leg bone, the researchers wanted to be able to see into the smoke cloud of detonation products. They needed to verify that the implosion remained symmetric to ensure an efficient detonation. Although it was a time when scientific breakthroughs came quickly, this challenge stumped them, and their initial efforts to use x-rays to visualize the event were limited.
When Health Outcomes Depend on More Than Medicine
Research shows how medical‑legal partnerships address legal and social needs during hospitalizations to support care and health outcomes.
New study recommends 1 alcoholic drink or fewer per day. Its researchers want clearer U.S. guidelines on drinking
One of the officials involved in the study commissioned by Biden's Democratic administration accused Trump's Republican administration of “sidelining” the research — an allegation the Trump administration denies.
A Scientific Achievement That’s Totally Random
Encryption systems rely on “random” numbers, but conventional computers can’t generate them perfectly. New research shows that quantum physics can.
New solar breakthroughs: the unexpected places scientists are finding revolutionary materials - Futura-Sciences
A Closer Look at Chemical Transformations The team’s breakthrough, recently published in the journal Nature Communications, is the scientific equivalent of pausing a movie in slow motion and noticing brand new characters on the screen. Instead of limiting themselves to the finished product of a reaction, the researchers examined every...
Police Removed Prominent Scientists from the ADA Meeting. Researchers Respond
The organizers of the American Diabetes Association meeting had a group of researchers removed from the event for sharing an editorial about negative impacts of policy changes to research funding.
WSU study finds father’s health before conception may affect future children
A father's health before conception may play a role in the future health of his children, according to new research from Washington State University.The study h
The Code As Witness: A Book About Science, Politics & Pandemic Inquiry
The Code as Witness written by Steven C. Quay is part scientific investigation, part policy strategy, and part warning about the future of biological research.
The Code As Witness: A Book About Science, Politics & Pandemic Inquiry
The Code as Witness written by Steven C. Quay is part scientific investigation, part policy strategy, and part warning about the future of biological research.
Scientists Unethically Experiment On the Unborn to Improve Gene Editing Techniques, Bioethicist Says
Genetic researchers are experimenting on unborn children in trials that could have been done on animal embryos, according to one bioethicist.
23 student researchers receive 2026 NSF fellowships - College of Arts and Sciences
The National Science Foundation awarded work in STEM-related fields such as artificial intelligence, biomedical engineering and marine ecology.
Drury chemistry professor lands $450,000 research grant from the National Science Foundation
SPRINGFIELD, Mo., June 9, 2026 – Drury University Assistant Professor of Chemistry Dr. John Kiernicki has received a $449,297 research grant from the National Science Foundation (NSF) for the study […]
Study links joint pain supplement to accelerating dementia
GAINESVILLE, Fla. — New research has found an association between taking glucosamine, a popular over-the-counter supplement used for joint pain, and a higher…
Sidelined U.S. study on alcohol's health effects published in independent journal
A study that found even low levels of drinking alcohol can increase health risks was published in full on Tuesday in an independent journal after being sidelined by the Trump Administration, which opted not to consider the federally-commissioned research to inform new U.S. drinking guidelines set out earlier this year.
U.S. Accounting Undergraduate Enrollment Continues to Outpace Growth Rate for Business Majors Overall
/PRNewswire/ -- Accounting undergraduate enrollment in U.S. colleges and universities showed strong growth in spring 2026 and continued to eclipse the...
NIH Bethesda Declaration report: politics hindering research
'The administration is attempting to change almost every aspect of how science is conducted in the United States,' one Nobel laureate said.
NIH Bethesda Declaration report: politics hindering research
'The administration is attempting to change almost every aspect of how science is conducted in the United States,' one Nobel laureate said.
NUTRITION 2026: The Leading Source for the Latest Science
NUTRITION 2026 puts science in the spotlight as thousands of nutrition researchers and health professionals convene for the the annual flagship meeting of the American Society for Nutrition. Qualifying journalists are invited to join the action July 25–28 in National Harbor, Maryland, just outside Washington, D.C.
The science of sweat: How a UF researcher is helping Brazil prepare for the heat of the World Cup
A UF scientist is using the science of sweat to help athletes perform, recover and stay healthy in extreme heat.
UTC postdoctoral researcher places second in CLEO Science Slam
Dr. Mohmad Junaid Ul Haq, a postdoctoral research associate in the University of Tennessee at Chattanooga Quantum Center, placed second in the annual CLEO Science Slam, which challenges scientists, students and postdoctoral researchers to present complex work in laser science, optics and quantum technology in a clear, engaging way.
Opinion: Does science need autonomous AI?
As technology developers and researchers rush to develop autonomous AI research tools (i.e., systems that independently perform tasks by designing their workflows and utilizing available tools) an urgent but rarely
Q&A: When is screen time healthy and when is it not?
Screen time is blamed for a lot of unhealthy outcomes, especially among children, but screen time can be used for a variety of things, from doom scrolling to learning and more. In this Q&A, Penn State researchers explain how people can consider what constitutes healthy or unhealthy screen use.
The Science Community Is Stepping Up. Let’s Go Bigger.
The scientific community is fighting a proposed change to research funding. Let's keep this momentum going to take on more attacks on science.
History of Science: Why is it important?
“The study of scientific history is vital for modern research, revealing that breakthroughs often stem from continuity rather than isolated revolutions”
Tokenomics will lead to opportunities in 'edge AI,' Citrini says
Citrini Research predicts that the economics of tokenmaxxing will prompt a shift to "edge AI" that will have implications for investors.
From early lab research to clinical treatments
Studies in mice can be helpful and important. They can point scientists toward new ideas. But they do not guarantee that the same thing will work in
The role of peer review
Modern peer review safeguards scientific quality yet is increasingly shaped by incentives, political priorities and funding challenges.
Alcohol’s Health Risks Accelerate After One Drink a Day, Study Finds
The alcohol industry has criticized the research, which found that even light drinking increases the risk of premature death.
BEACON: How Benchmarking Combats the Reproducibility Crisis in Modern Science
A new initiative called BEACON aims to advance scientific reproducibility by uniting siloed benchmarking efforts across biomedical research.
NASA Spaceline Current Awareness List #1,203 5 June 2026 (Space Life Science Research Results)
NASA Spaceline Current Awareness List
University of Miami joins new NOAA Cooperative Institute to advance sustainable U.S. aquaculture
Rosenstiel School researchers will contribute expertise in ocean science, environmental forecasting, and aquaculture innovation through a national partnership focused on strengthening America's seafood supply.
A reporting checklist for large language models in behavioural science
Nature Human Behaviour - Large language models offer new opportunities for behavioural science, but their rapid evolution poses challenges for research rigour. We introduce a consensus-based...
Mylpf protein serves as a molecular linchpin for muscle health
University of Maine researchers have published new findings about how muscles form, why certain muscle diseases develop and why symptoms may not appear until years after muscle degeneration begins.
We can create the future of science right now
Paul Litvak is the founder and Executive Director of the Robyn Dawes Institute and a Visiting Scholar at UC Berkeley. He has a PhD in Behavioral Decision Research from Carnegie Mellon where he studied emotions and the sunk cost bias. Over 15 years in industry, he solved a wide range of challenging technical problems. At Meta he created models optimizing the ad review process. At Google he ran experiments to measure social influence. At Airbnb, he was a product manager leading machine learning teams optimizing search ranking and price suggestions. He also co-founded and led product at Rhythmic Health, a venture-backed biosensing startup, creating an accurate low cost system using a color changing strip and a smart phone to measure salivary lactate. The bottleneck At this point, it is uncontroversial to say that science needs to stop using the PDF article as the unit of knowledge and currency. The unbearable slowness of scientific publishing, the profit motive and margins: I’m not saying anything new. The PDF also sucks because it’s hard to extract structured information, which makes it hard to do evidence synthesis. As a result, we do much less evidence synthesis than is needed. And evidence synthesis ultimately undergirds most policy and medical decision-making. I can see second-by-second real-time odds for any sporting or newsworthy event, but a school board can’t see the best evidence on whether their 8th graders should be taught algebra. As a society, we don’t treat this as an important problem. Again, not controversial. Not only is the problem well understood, but the solution has already been laid out. What we need is AI-assisted living evidence synthesis - (1) an open knowledge graph of atomic claims, (2) claims linked to evidence, (3) assessment and synthesis of each piece of evidence, and (4) continuous updating with new data. What few realize (yet) is that the technical capacity to build this vision for a significant portion of science already exists. Not only that, scientists and startup teams are already building many of these components. I know this because I’ve been surveying the space and talking to many of the builders. There are some missing pieces: for example, evaluations of how well some of the components work. But at this point, most of what’s missing is a fully end-to-end working integration of all of these parts. In the rest of this essay, I’m going to lay out all the parts of a working living evidence layer for science and who is working on them, and propose concrete next steps for building this system. What’s now possible The diagram above outlines the components of a living evidence synthesis platform, including some of the teams working on each component1. Scientific PDFs are processed into claims with associated evidence. The evidence is subjected to a forensic audit, methodological evaluation and robustness and reproducibility checks. Finally it’s given a weight in a continuously updating synthesis. What follows is a description and status of each component and a few of the teams working on them. Document understanding The first thing you need to be able to do is turn an article into structured data. Mostly that means parsing PDFs. There are often multicolumn layouts that confuse non-specialized PDF to text processing libraries. For scientific papers, there is the added complexity of parsing formulas and tables and figures. This is a really hot area - there are startups offering APIs, and it seems like a new open source package gets posted to Github every few weeks. What follows isn’t exhaustive. A package called GROBID was the state of the art for a while, they didn’t update their package for nearly two years until very recently. In the meantime reducto.ai released an AI powered PDF extraction API, PaddleOCR became popular, IBM released a model called Docling, and both Mistral and Gemini created models and libraries. I also know of at least one other well-funded psychology research group working on a paper parser. By contrast, there are few open evals in this space, with no extensive evals for complex table comprehension in particular. Nonetheless, I’m confident this will be a solved problem soon, given the combination of LLM advances and developer interest. Hypothesis level extraction There has been increasing interest in comprehending the extracted text of papers and linking information to evidence for each hypothesis. A lot of work has already been done. Trialstreamer (Marshall et al. 2020) and RobotReviewer LIVE (Marshall et al. 2023) demonstrated automated extraction of trial population, intervention, and outcome at scale on clinical RCTs. PaperQA2 (Skarlinski et al. 2024) and Ai2 ScholarQA (2024) extended this to retrieval-augmented question answering with citation grounding. Elicit, Consensus, and SciSpace operationalized claim-level extraction for end users. OpenEval (Booeshaghi et al. 2026) is the most recent and most ambitious: 1.96 million atomic claims extracted from 16,087 eLife manuscripts using Claude Sonnet 4.5, grouped into ~299,000 results, with LLM evaluations showing 81% agreement with human peer review on a 2,487-paper subset. None of these solutions link claims to test-statistics, as you would need to evaluate randomized controlled trials. This is why I built the evidence.guide API - to extract hypotheses and associated test statistics from behavioral science papers. The best public eval of this kind of extraction I’m aware of comes from the recent SCORE project - they had humans code thousands of psychology papers to extract their claims by hand. It would be extremely helpful to the world if all scientific PDFs were available as structured open data. I’ve been working to make this happen, both directly at Berkeley and through coordination with large entities I can’t yet speak of; as hard as it is to do, I think it’s possible2. Forensic audit A lot of work has been done on forensic audit, but some gaps remain. Of course, for biology papers that rely on images for evidence, there are a variety of tools (notably Proofig and ImageTwin) to spot anomalies. These are still well short of what sleuths like Elizabeth Bik can do on her own, but these tools are constant companions among fraud analysts. There’s someone working on auditing Excel files for anomalies, and a number of teams are automating numerical checks like GRIM and SPRITE, including Scrutiny project, the INSPECT-SR team as well as statcheck. The regcheck team is building a way to use AI to compare preregistrations to analyses in papers, to ensure there aren’t significant deviations. Nonetheless, there are many other kinds of anomalies to screen for, both public and less publicly known. And there are no formal evals for anomaly detection that I’m aware of. Still, there’s a lot to draw from in this space and I’m pretty certain we will be able to scan papers for most kinds of obvious anomalies in the near future. Methodological review This area has been white hot, though I fear for many of the startups in this space, because this capability may become commoditized. There are at least six different AI peer review companies, including Refine.ink, Reviewer3, ReviewerZero.ai, Q.E.D. Science, Paper Wizard, and Isitcredible. Coarse (a pun on refine) was also recently created as an open source alternative. These systems provide qualitative feedback on the content of papers, spotting methodological weaknesses and mathematical errors. They seem to work pretty well, and many academics report bitterly that they exceed the average quality of typical peer reviewers. But there are few evals here either. What evals exist so far involve using LLM-as-judge (circularity problems abound) or comparing against human reviews of questionable quality. What you’d ideally want is an eval that measures capturing known errors in papers3. Reproducibility and robustness Another active area has been using AI agents to automate computational reproducibility4 and robustness5 checks in papers that report numerical results. For more recent papers where data and code are available, AI agents can see whether they can re-run the analyses and produce the numbers reported in the published paper. In addition to a handful of individual academics who have been experimenting using Claude Code for this, the Institute for Replication is a leading group working on building an end to end system. The evals related to this problem are the most mature, with CORE-Bench (Siegel, Kapoor, Narayanan 2024) and PaperBench (OpenAI 2025) available to benchmark agents on this task. There is also work on getting AI agents to test alternative ways of analyzing the data to ensure the results are robust to small analytic design choices. Synthesis This is the most underdeveloped area where significant investment is required. Although some automated evidence synthesis systems exist — for example, otto-sr is building an AI agent to write systematic reviews — none of these incorporate the full range of paper level signals to weight evidence appropriately. Nor is there anything like an eval or a gold standard for a good systematic review. Arguably Cochrane reviews are the closest we have to gold standard human systematic reviews, though I’ve heard academics in the know complain about their uneven quality. A key question for a synthesis platform is how to weight anomalies and methodological issues in assessing the quality of a piece of evidence. This is an unsolved problem and one I’m very keen to work on. Continuous updating There are many pieces of basic infrastructure available for monitoring for new research and initiating updates. OpenAlex is the current open citation graph. Retraction Watch integrated into Crossref in October 2023. Scite tracks how citations support, contrast, or mention prior claims. The Living Evidence Network demonstrated continuous-update workflows in clinical guidelines. Engineering this is a relatively straightforward task. When you look over this technical architecture and all the progress being made, it’s hard not to be optimistic that a living guide to scientific evidence will be built. The stakeholders are ready The social infrastructure for this is starting to coalesce — it’s not just a pie in the sky academic exercise to imagine this coming into existence. Institutions like the Center for Open Science, the Institute for Replication, the INSPECT-SR, the Living Evidence Network and more are all working on scaling work to improve research quality. Funders are also aligned. The Sloan Foundation has funded living evidence work through COS. Coefficient Giving supports the Institute for Replication and COS. The Astera Institute and the Institute for Progress have shown interest in this space. NIH has established an Office for Replication and Reproducibility. Although there are (very unfortunately) serious headwinds in science funding generally, there is an active group of funders interested in metascience. A brief word about what I’ve been doing at RDI. First, as a Visiting Scholar at Berkeley I’ve been actively figuring out how a non-profit and a public university can conduct and make public the results of large-scale academic article data mining. With some of the money I raised from donors, I commissioned a legal analysis of recent case law and publisher text data mining (TDM) agreements in order to understand whether a massive open data mining of academic articles is possible (with caveats, it is). I’ve also been working to bring together stakeholders in this space, and identify gaps. I’ve also been doing some software development in this space, with more to come. A pilot proposal The assumption undergirding all of this is that an AI, given all this information, would make the right judgment about a scientific claim with lots of conflicting evidence, weighing all the factors appropriately. That’s the hypothesis we need to test. Randomized control trial research is the best place to focus on first. RCTs are used to make many of the important decisions in society - from medical trials to public policy changes. And they use a relatively uniform set of inferential statistics with lots of known and available diagnostics. Behavioral science experiments, within the broader realm of RCTs, should be first used as a testbed whose results can be generalized. Because behavioral science is at the vanguard of open science practices, replications abound (there are thousands of them) to serve as ground truth training data. Key Hypothesis Therefore the pilot would test, in behavioral RCTs that have been replicated, whether the quality of evidence for a claim can be used to accurately predict whether that claim will replicate. Secondary Hypotheses Compared to claims that replicated, non-replicated claims demonstrate a greater share of forensic anomalies in their source literatures. Hypothesis level claim and statistic extraction is accurate enough to scale living evidence without onerous human review costs. Replication prediction is more accurate than prediction markets6 or journal prestige. If all the different quality signals we gather do accurately predict which studies will replicate, then we can use that model to score evidence to power the living evidence layer. Why this is informative regardless of outcome If the pilot succeeds, the architecture extends to medical RCTs (where Living Evidence already operates and integration is mostly about claim representation), then to slices of basic biology with stable replication structure. If it fails, the field learns which quality signals are load-bearing and which ones metascience has oversold. Either result is a contribution to knowing what the literature supports. Implications for funders Because this burgeoning ecosystem of builders already exists, a well-informed philanthropic or government funder could play a crucial catalyzing role in bringing this future about. They could play at least three roles: creating open structured datasets, publishing open benchmarks and incentivizing the solving of key technical challenges. First, open archives of papers that the government maintains, like PubMed, could be turned into structured data amenable to large scale metascience and claim aggregation. I know the US government already has an interest in doing this, though some key open questions remain unanswered. How do you determine the best models and systems for accurately extracting information from papers? How can you establish a robust way to allow researchers to flag errors and correct them? And finally, how do you create a legal regime in working with publishers to maximize the scope of available papers? For the latter, a university or a private philanthropy may be better positioned to make structured data publicly available under journal subscription terms or fair use. Philanthropists or government funders could also coordinate to create or commission benchmarks that evaluate whether important problems have been solved. For example, an open benchmark for claim extraction from a range of different scientific article types would be extremely helpful. Ensuring the underlying data are accurate is vital for creating these evaluations. I’ve discussed opportunistically using various human-created datasets for this purpose, but a consistent problem is that errors in human data make it difficult for them to serve as a gold standard. Finally, with structured data and benchmarks available, the government or private philanthropy could use them to incentivize groups to develop machine learning systems that meet these benchmarks. Prizes are one potentially valuable tool for this. For example, you could establish a prize for a system that accurately updates a living meta-analysis for a small set of claims. Prizes are particularly useful as signals of problem importance, and can help create vibrant ecosystems of public and private research—see, for example the role the government played in kickstarting the current work on nuclear fusion. Conclusion The drawbacks of the current scientific publishing system are known. Scientists agree, metascientists agree, philanthropists agree: the published PDF plus citation graph isn’t the right substrate for maintaining a representation of the evidence base in science. The pieces needed to build the alternative either already exist or are rapidly taking shape. The community is forming around exactly this problem, with concrete partnerships and shared infrastructure. A pilot should start on behavioral science RCTs because that’s the slice of empirical science most amenable to legibility, where replication ground truth is richest, and where the failure modes are best documented. What’s been missing is the galvanizing mission to assemble these pieces into something that works. That’s what I’m proposing to build. *** 1 I have a broader field map that I’ll release publicly soon. This is me, building in public! 2 If this is something that you are excited about, please reach out and talk to me. 3 More on this very soon too! 4 This tests whether, given the code and the data, you can get the same statistics as reported in the published paper. 5 This tests whether the results are the same as a paper’s given alternative analytical decisions in conducting the analysis (like outlier omission). Closely related is the idea of a “multiverse” where you come up with many different ways of answering the same underlying research question with the same data, and test whether the results hold in all those alternative methods. There’s been work on the latter as well. 6 Some of the replications, e.g. those from the SCORE project, had paired the experiments with forecasts from prediction markets. So we get to look at this for free.
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