PubPeer is sometimes discussed as if it is some kind of cesspit where people smear honest scientists with specious allegations of fraud. I'm always taken aback when I hear this, since it is totally at odds with my experience. When I conducted an analysis of PubPeer comments concerning papers from UK universities published over a two-year period, I found that all 345 of them conformed to PubPeer's guidelines, which require comments to contain only "Facts, logic and publicly verifiable information". There were examples where another commenter, sometimes an author, rebutted a comment convincingly. In other cases, the discussion concerned highly technical aspects of research, where even experts may disagree. Clearly, PubPeer comments are not infallible evidence of problems, but in my experience, they are strictly moderated and often draw attention to serious errors in published work.
The Problematic Paper Screener (PPS) is a beautiful resource that is ideal to investigate PubPeer's impact. It not only collates information on articles that are annulled (an umbrella term coined to encompass retractions, removals, or withdrawals), but it also cross-references this information with PubPeer, so you can see which articles have comments. Furthermore, it provides the citation count of each article, based on Dimensions.
The PPS lists over 134,000 annulled papers; I wanted to see what proportion of retractions/withdrawals were preceded by a PubPeer comment. To make the task tractable, I focused on articles that had at least 100 citations, and which were annulled between 2021 and 2025. This gave a total of 800 articles, covering all scientific disciplines. It was necessary to read the PubPeer comments for each of these, because many comments occur after retraction, and serve solely to record the retraction on PubPeer. Accordingly, I coded each paper in terms of whether the first PubPeer comment preceded or followed the annulment.
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| Flowchart of analysis of PPS annulled papers |
I had anticipated that around 10-20% of these annulled articles would have associated PubPeer comments; this proved to be a considerable underestimate. In fact, 58% of highly-cited papers that were annulled between 2021-2025 had prior PubPeer comments. Funnily enough, shortly after I'd started this analysis, I saw this comment on Slack by Achal Agrawal: "I was wondering if there is any study on what percentage of retractions happen thanks to sleuths. I have a feeling that at least around 50% of the retractions happen thanks to the work of 10 sleuths." Achal's estimate of the percentage of flagged papers was much closer than mine. But what about the number of sleuths who were responsible?
It's not possible to give more than a rough estimate of the contribution of individual commenters. Many of them use pseudonyms (some people even use a different pseudonym for each post they submit), and combinations of individuals often contributed comments on a single article. Some of the PubPeer comments had been submitted in early years, when they were just labelled as "Unregistered submission" or "Peer 1" etc., so any estimate will be imperfect. The best I could do was to focus just on the first comment for each article, excluding any comments occurring after a retraction. Of those who had stable names or pseudonyms, the 10 most prolific commenters had commented on between 9 and 50 articles, accounting for 27% of all retractions in this sample. Although this is a lower proportion than Achal's estimate, it's an impressive number, especially when you bear in mind that there were many comments from unknown contributors, and the analysis focused only on articles with at least 100 citations.
Of course, the naysayers may reply and say that this just goes to show that the sleuths who comment on articles are effective in causing retractions, not that they are accurate. To that I can only reply that publishers/journals are very reluctant to retract articles: they may regard it as reputationally damaging, and be concerned about litigation from disgruntled authors. In addition, they have to go through due process and it takes up a lot of resources to make the necessary checks and modify the publication record. They don't do it lightly, and often don't do it at all, despite clear evidence of serious error in an article (see, e.g. Grey et al, 2025).
If an article is going to be retracted, it is better that it is done sooner rather than later. Monitoring PubPeer would be a good way of cleaning up a polluted literature - in the interests of all of us. Any publisher can do that for free: just ask an employee of the integrity department to check new PubPeer posts every day—about 40 minutes and you’re done. PubPeer also provides publishers with a convenient dashboard to facilitate this essential monitoring task.
It would be interesting to extend the analysis to less highly-cited papers, but this would be a huge exercise, particularly since this would include many paper-milled articles from mass retractions. I hope that my selective analysis will at least demonstrate that those who comment on problematic articles on PubPeer should be taken seriously.
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