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More science friction for less science fiction

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  • Jennifer A Byrne
  • Stefan Stender

Abstract

AI-ready health datasets can be exploited to generate many research articles with potentially limited scientific value. A study in PLOS Biology highlights this problem, by describing a recent, sudden explosion in papers analyzing the NHANES health dataset.A new study by Suchak et al. describes a sudden, recent explosion in papers analyzing the NHANES health dataset, where similar manuscripts have been described as overwhelming processes at some journals. In this accompanying Primer article, we summarize the study's findings and recommendations. We outline practical steps that publishers, journals, peer reviewers and readers can take to better recognize similarly formulaic, low-value submissions and publications to reduce their research impacts.

Suggested Citation

  • Jennifer A Byrne & Stefan Stender, 2025. "More science friction for less science fiction," PLOS Biology, Public Library of Science, vol. 23(5), pages 1-4, May.
    • Handle: RePEc:plo:pbio00:3003167
    DOI: 10.1371/journal.pbio.3003167
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    References listed on IDEAS

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    1. John P A Ioannidis & Christine Q Chang & Tram Kim Lam & Sheri D Schully & Muin J Khoury, 2013. "The Geometric Increase in Meta-Analyses from China in the Genomic Era," PLOS ONE, Public Library of Science, vol. 8(6), pages 1-8, June.
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