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#scientificpublication — Public Fediverse posts

Live and recent posts from across the Fediverse tagged #scientificpublication, aggregated by home.social.

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  1. “Science is a cooperative enterprise spanning the generations… a community of minds, reaching back to antiquity and forward to the stars”*…

    The sharing of experimental results and the underlying data is critical to the advance of science. Indeed, when I had the chance to do a scenario planning exercise with a collection of the leading research university librarians in the U.S. a couple of decades ago, the biggest threat/fear they surfaced was the concern that the free and open exchange of ideas and data, as manifest formally in scientific publication and informally in the collegial cooperation among scientists, would be occluded by an increasing proprietary embrace of knowledge.

    73% of geneticists surveyed in an article in the 23/30 January 2002 issue of the Journal of the American Medical Association agreed that although keeping data private may help the individual researcher, data hoarding is detrimental to the progress of science Still, sadly, that threat has grown since the turn of the millennium.

    By way of current (and dramatic) example: as Celina Zhao reports, more than half of AI “unicorns” have never published a paper or preprint…

    Today’s biggest artificial intelligence (AI) startups make no shortage of bold promises. Their technologies, some boast, will revolutionize software development, drug discovery, and scientific research.

    Yet a new preprint posted on 16 July on bioRxiv suggests many of these firms barely participate in one of science’s most fundamental practices: publicly documenting discoveries in scientific literature so other researchers can evaluate and build on them. More than half of AI unicorns—private companies valued at more than $1 billion—have never played a leading role in publishing a scientific paper or preprint, according to the new analysis. Collectively, they accounted for just one in every 1000 AI papers published in 2025.

    “For a field that is supposedly reshaping science and is so advanced in terms of scientific potential, not having any scientific documentation seems like a very weird paradox,” says paper co-author John Ioannidis, a metascientist at Stanford University [see here]. “How can you judge that what they say is real, validated, and reproducible?” The scarcity of publications, others say, also makes it harder to assess AI’s social impacts, including energy use and safety.

    But University of Alberta AI ethicist Mohamed Abdalla says the findings reflect the incentives facing commercial AI developers, rather than solely a failure to uphold scientific norms. “It’s not the company’s job to advance science, right?” he says. “The company’s job is to advance money.”

    Ioannidis has long studied how unicorns, particularly in biotech, engage with the scientific literature. (In 2015, he was the first to publicly scrutinize the lack of peer-reviewed studies produced by Theranos, the blood testing startup that proved to be based on fraudulent data.) He wondered whether AI unicorns would show similar patterns.

    To find out, he and his team first identified all 317 unicorn AI companies that have existed from 1998 to 2025. Then, they searched for publications affiliated with these startups—including journal articles, conference papers, reviews, and preprints. They selected those where a company researcher played a leading role as a first or last author, indicating the startup had made a substantial contribution to the work. The final data set included 2077 final publications, comprising 1389 peer-reviewed papers and 688 preprints.

    More than half of the startups had never produced a single qualifying paper, the analysis revealed. Scientific influence proved even more concentrated, with the top 5% of firms accounting for greater than 90% of all citations. OpenAI alone was responsible for nearly 40% of all citations in the data set, followed by the Chinese computer vision company Megvii and the platform Hugging Face. And even at the most prolific companies, much of the output came from the same small group of repeat authors. For example, despite OpenAI employing roughly 4500 people, only eight researchers had authored five or more qualifying papers.

    The findings are unsurprising to some AI researchers given how the industry is structured. For example, unlike the pharmaceutical industry, where published discoveries can be protected by patents, AI companies have learned they often gain little from publicly disclosing technical advances, says Nur Ahmed, an AI researcher at the University of Arkansas. Google’s landmark 2017 paper on the transformer—the architecture that underpins today’s large language models—has become a classic cautionary example, Abdalla adds. Although Google patented aspects of the technology, “I don’t think anybody’s paying Google for that,” he says.

    Startups also operate on much faster timelines than academia, where peer review can lumber on for months or even years. That’s why many AI companies have embraced what Avijit Ghosh, an AI policy researcher at Hugging Face, calls the “blogification” of research: announcing new models and releasing code or data sets through blog posts and technical reports rather than scientific journals. The new analysis didn’t track those outputs, he points out.

    For Ghosh, the debate shouldn’t center on publishing in journals versus blogs. What matters is whether companies are releasing enough code, data sets, or model weights (the numbers that determine how a model interprets and responds to a prompt) for others to independently verify and build on their work, he says.

    The preprint also found that firms based in China consistently published more papers than their counterparts based in the United States. Whereas leading U.S. frontier labs have increasingly kept the details of their most capable models secret or “closed sourced,” leading Chinese companies have embraced “open-source” models. Moonshot AI, one of the Chinese startups included in the study, recently unveiled Kimi K3—one of the strongest open models to date—and publicly released its model weights through Hugging Face today.

    But whether models are open or closed, the rapid pace toward increasingly powerful generalist AI worries Emma Pierson, a computer scientist at the University of California, Berkeley. She argues AI research—whether published freely or kept secret—risks accelerating models that pose serious societal and safety concerns, including supercharging cyberattacks. “If we were racing forward on cancer-curing AI, I would be like, ’Fantastic, full steam ahead,’” she says. “But that’s not what we’re racing toward, right?”…

    The secretive unicorns: “AI’s top startups are barely publishing their research,” from @science.org.

    By way of example? In order to have a broader footprint in AI for (default proprietary) scientific discovery, Google moves away from a successful AI effort (that did publish): “Google DeepMind dismantles Nobel-winning AlphaFold team in strategy shift” (gift article from the FT). One wonders: when these LLMs run out of published papers on which to train, where (and how) will they source the knowledge they need to stay useful?

    * Neil deGrasse Tyson

    ###

    As we share and share alike, we might recall that it was on this date in 1887 that Chester A. Hodge of Beloit, Wisconsin received patent No. 367,398 for ‘spur rowel’ barbed wire (consisting of spur shaped wheels with 8 or 10 points mounted between 2 wires).  It was one of many patents for barbed wire (e.g., here), which spread across the American West rapidly (thanks, in no small measure to the guy featured in the almanac entry here)– and (by protecting farmers from foraging free-ranging cattle) paved the way for the expansion of wheat (and other kinds of) farming… even as it spelled the doom of a commons– the open range.

    Roll of modern agricultural barbed wire (source) #academicCommunications #academicResearch #AI #artificialIntelligence #barbedWire #ChesterHodge #commons #cooperation #culture #history #openRange #research #Science #scientificJournals #scientificPapers #scientificPublication #scientificPublishing #scientificResearch #Technology
  2. Hey #AcademicFedi I need your opinion on something 🙏

    I was recently asked to review on a platform I did not know: qeios.com

    Anyone knows about it? It did not seem too fishy at a glance but their economic model and who is behind it is not entirely clear to me so I'm a bit wary of potential link with people with an agenda (almost got bitten before).
    So I'm not sure I want to encourage people to use that can of platform instead of, say, @PeerCommunityIn until I know more about them and the guarantees that all the content will not be lost five years from now...

    All opinions, feedbacks, or boosts are welcome 🙂

    #academia #academicChatter #ESR #helpESR #askESR #review #journal #publication #scientificPublication #scientificPublishers

  3. Hey academic Fedi,
    I'm regularly thinking that it would be useful to have a tool that helps me find articles that cite a paper to contradict (or at least "contrast") its result.

    It seems that scite [1] does this but they requires a pretty steep subscription given that I'm not sure how reliable their tool is and that they also advertise a chatbot...

    [1]: scite.ai

    Does anyone know of something similar, or a workaround to achieve something similar using standard scientific search engines?

    If you don't know, boosts are also appreciated to help the person who might know see this post 😉

    #academicChatter #academia #scientificPublication #citations #research #academicMastodon #AcademicFedi #AcademicFediverse

  4. @clairemathieu

    😱 Depuis quand un gouvernement peut-il décider de ce que les scientifiques peuvent ou ne peuvent pas publier??

    Since when can governments decide what should be published or not by scientists??

    Resist the censorship!!
    #UsPol #Science #ScientificPublication

  5. Call for Papers: The special issue Environmental DNA: New Horizons in Aquatic Sciences, Terrestrial Ecology, and Beyond invites research on innovative eDNA methodologies, biodiversity monitoring, and ecological dynamics. Submit by October 1, 2025. Hosted by Ecology and Evolution & Aquaculture, Fish, and Fisheries.

    #eDNAResearch #ScientificPublication #science #research

    🔗: bit.ly/4hM3667

  6. Here is a question for writers of scientific papers, or others who have to cite sources in their writing. If you have a situation where a person, in this case Alan Bartholomai, who writes a personal communication to an author, in this case Eugene Gaffney, and that author then reproduces the letter in a publication, how does one correctly cite information contained within the letter?
    Would it be "(A. Bartholomai pers. comm to Gaffney in Gaffney, 1981)" ?

    #ScientificPublication

  7. "To further boost online engagement, scientists may also be incentivized to review pre-prints. Recent reports suggest that scientists are more motivated to review if they are credited for it, especially if these efforts are recognized by their employers; monetary compensation ranked only sixth"
    #Preprint #scientificpublication #PeerReview

    embopress.org/doi/full/10.1525

  8. "Importantly, being an author is not only about credit but also about accountability. Typically, an author will be accountable for the quality and integrity of their own contribution, but also for the work as a whole by ensuring that questions arising post-publication are investigated thoroughly and that materials and data remain available."

    #ResearchAssessment #ResearchIntegrity #ScientificPublication

    journals.plos.org/plosbiology/

  9. Bernd has been pushing this point for a while, and I think he is right. Self correction is an important part of the scientific process and journals, funders, and institutions need to do more to encourage it.

    'What can journals do to support both self-correction by authors and by the community? We have discussed this matter for a decade at EMBO Press, culminating in a workshop that recommended to make an explicit distinction between an author initiated- and an externally initiated- or even forced retraction. We use the term “withdrawal” for the former and reserve “retraction” for the latter.'
    #scientificpublication #ResearchIntegrity
    @emboreports

    embopress.org/doi/full/10.1525

  10. PNAS commentary on the first year of their Consultative Peer Review Pilot

    'The pilot is designed to encourage the submission of research that is sufficiently multidisciplinary and presents a challenge in finding reviewers, is counter to a prevailing view, or is too far ahead of its time to receive a fair review. Authors whose work qualifies for this review option can submit through the pilot to have their work thoroughly and efficiently reviewed by experts in the fields most relevant to their research.'
    #PeerReview #sciencecommunication #scientificpublication

    pnas.org/post/update/one-year-

  11. A privilege to work with @richardsever on this brief commentary piece on preprints, peer review & the special problems posed by medical/clinical manuscripts.
    (it should be open access).

    #Preprints #PeerReview #RefereedPreprints #scientificpublication

    actamedicaportuguesa.com/revis

  12. "The ideal of self-correction in science is not well served by the current culture and system surrounding amendments to published literature. Here we describe our view of how amendments could and should work by drawing on the idea of an author-led version control system."

    #ScientificPublication

    royalsocietypublishing.org/doi

  13. @PeerCommunityIn 3/3 With a donation equivalent to the publication fees - #APC- of a single article in a gold #openaccess journal, institutions can contribute to make this public #scientificpublication system sustainable 🎯. Not a supporter yet? Check our post at peercommunityin.org/2021/02/24

  14. Focused on STEM research, not social science, but a worthwhile critical examination of whether or not peer review is really everything it is cracked up to be.

    "Why don’t reviewers catch basic errors and blatant fraud? One reason is that they almost never look at the data behind the papers they review, which is exactly where the errors and fraud are most likely to be."

    experimentalhistory.substack.c

    #PeerReview #Science #Research #ScientificPublication

  15. Place your bets

    "To try to prove our own brilliance scientifically (before we are replaced by machine learning) is a challenge few editors would be able to resist, and we were no different. We thus set out to test our ability to predict citations of unpublished research papers submitted to The BMJ."

    #ScientificPublication #PeerReview #ScientificEditor

    bmj.com/content/379/bmj-2022-0

  16. 'Fifteen scientific journals published a total of 812 (68.7%) of all 1182 papers retracted for being paper mill papers, and 166 (14.0%) were published in one journal, the European Review for Medicaland Pharmacological Sciences. Of these, all journals appear to be non-predatory journals.'

    #ScientificPublication #PaperMills #ResearchIntegrity #PeerReview

    bmj.com/content/379/bmj-2022-0

  17. #ResearchPaper #scientificpublication #publishers At some point we will have to talk, seriously, about all those papers published by invitation, special issues, and all the rest, whose messages are constantly flooding our incoming folders. Sooner or later we will end up coauthoring one or few of them. But, IMHO, we should be very careful about founding a scientific career on them. You might be caught by surprise if a given assessing committee does not value them as you might have expected.