Critics of birdsong study fight to be named in Nature’s retraction

A zebra finch in New South Wales, Australia. Source: JJ Harrison/Wikimedia Commons (CC BY-SA 4.0)

Researchers who flagged methodological issues in a paper on birdsong a year and a half before Nature retracted it say they should be credited in the editorial notice. But the editors have refused, with one telling the critics the paper was retracted for unrelated reasons.

The March 2024 study at the center of the dispute looked at how sexual selection may drive song patterns in male zebra finches. Nature retracted the paper last month because two of the synthetic song pairs used in the study were found to be unreliable, according to the notice. All three authors agreed to the retraction. 

Todd Roberts, the paper’s corresponding author, told Retraction Watch the critics now asking for credit “prompted us to check the synthetic song pairs used in our paper.” He said his team did not do the reliability analysis of the pairs until after publication.

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Widely criticized keto diet study retracted

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A 2025 paper claiming the keto diet does not promote the formation of arterial plaques has been retracted after widespread criticism of the study’s methods and claims. The journal found “the identified errors are too great to be corrected with a corrigendum,” according to the March 11 retraction notice.

In April 2025, JACC: Advances published the study, which looked at plaque build-up in 100 otherwise generally healthy people who had experienced an increase in their cholesterol levels while being on a keto diet. The study claimed scans performed one year apart by the company Cleerly showed the diet was not associated with the development of arterial plaques. 

This finding went against what previous studies had found, and it led to what Wired called “a new war in the nutrition world.” 

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How the media hypes “research that is absurd on its face”

Aaron Brown says his new book, Wrong Number: How to Extract Truth from a Blizzard of Quantitative Disinformation, “isn’t an exposé of fraud—Retraction Watch covers that ground. It’s about legitimate-looking research that is absurd on its face.” 

Published this month by Wiley, Brown uses dozens of case studies to show “why widely reported and influential studies in top journals are not just wrong, but obviously and egregiously illogical or contrary to simple fact. My focus is less on the policy and statistical errors than on why no one seems to care,” he says.

Brown is a risk manager working in hedge fund management. He also teaches statistics at New York University and the University of California San Diego and writes columns for Reason and Bloomberg, among other outlets. We asked him to tell us more about how he thinks about the nexus of science, journalism and the publish-or-perish system that also pushes researchers to engage with non-experts to promote their work.

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‘Comically bad’ datasets used to train clinical models for stroke and diabetes 

A dataset on Kaggle purportedly showing people who have had a stroke includes images of Sylvester Stallone from Rambo and other celebrities. Source

Scrolling through an online image dataset, Adrian Barnett, a statistician at the Queensland University of Technology in Australia, pointed out a few familiar faces. Sylvester Stallone as Rambo, and then again on the red carpet. “This is just ridiculous,” Barnett said. George Clooney, Angelina Jolie and Daniel Craig all appear more than once, often with the same image. “You can see,” Barnett said, “this is just a comically bad dataset.”

This particular dataset, collected in a folder titled “droopy” and hosted on an open-source repository called Kaggle, underpins a paper published in Scientific Reports – not as a find-the-celebrity game, but as a training set for a predictive clinical model for early detection of strokes. 

The paper is the most recent example of a much wider problem that Barnett and his Ph.D. student Alexander Gibson have documented with Kaggle, which is owned by Google and hosts datasets uploaded by users that researchers and machine learning practitioners can use to build predictive models. By examining two other Kaggle datasets on stroke and diabetes, both of which included tabular patient data, Gibson and Barnett traced how the data move through the scientific literature and in some cases, into clinical use. Their work, described in a preprint posted to medRxiv in February, already has led to several retractions of the papers using these dubious datasets. 

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Are AI chatbots infiltrating online survey data? Not yet, says new study

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Despite concerns some have raised about potentially compromised data, AI chatbots aren’t yet completing online research surveys widely, according to a new preprint. 

The authors of the study, posted earlier this month on PsyArXiv, found that fewer than 1% of around 4,800 survey responses collected by 12 different companies contained text that was likely not written by a human. Among 400 responses from a 13th company, however, around 16% were flagged for possibly being completed by a chatbot. 

The study used a novel detection tool created by the survey research company Prolific, which funded the project.

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Bloodhound code sniffs out copied-and-pasted numerical data

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Markus Englund, a software developer and sleuth based in the Netherlands, first hit paydirt with invasive plant species in China. After having scanned 12 other published scientific datasets with his novel detection software with no results, he came across one showing something suspicious: rows and rows of measurements of plant roots repeated across entirely different species. 

“I was really excited,” he said in a recent call with Retraction Watch. “I couldn’t think of any innocent explanation for why that would be the case.” 

Englund had built a tool dedicated to “purging” fabricated data by identifying “impossible” data in spreadsheets available on open repositories, according to Science Detective, his site about the initiative. From his initial review, he has found 18 datasets containing duplicated values that are possibly serious enough to need correcting — including one from an influential paper on Parkinson’s disease, as The Transmitter recently reported. (Retraction Watch’s cofounder Ivan Oransky is that publication’s editor-in-chief.)

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BMJ retracts cardiac stem cell paper, removes authors months after sleuths flag data ‘mismatch’

The BMJ has retracted a paper on stem cell therapy for heart failure after sleuths flagged the work for “serious” inconsistencies in data.

Published in October, the paper reported the results of a phase III clinical trial of more than 400 patients in Shiraz, Iran, looking at whether stem cell therapy lowers the risk of heart failure after a heart attack. The journal announced the results in a press release, and news of the findings appeared in several outlets. New Scientist called the study the “strongest evidence yet that stem cells can help the heart repair itself.”

A week after the study was published, sleuths took to PubPeer to point out inconsistencies between the data reported in the article and the dataset uploaded with it. The concerns included a “curious repeating pattern” of records in the dataset and a high number of integers for the height and weight of patients. 

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Lawsuit fails to block retraction of paper claiming to link heart-related deaths to COVID-19 vaccines

Greg J. Marchand in a photo from his research institute’s website.

A Taylor & Francis journal has retracted a widely-read paper linking cardiac-related mortality to COVID-19 vaccines after an unsuccessful legal attempt by the lead author to block the withdrawal. That author says he is considering further legal action against the publisher.

The article, “Risk of all-cause and cardiac-related mortality after vaccination against COVID-19: A meta-analysis of self-controlled case series studies,” drew swift criticism when it was published in Human Vaccines & Immunotherapeutics in August 2023. At the time, critics and sleuths were quick to challenge the data and methods used in the paper, which now has more than 143,000 views on the Taylor & Francis website and has been cited 15 times, including by two letters to the editor of the journal and a response from the authors, according to Clarivate’s Web of Science. 

The retraction notice, posted online January 16, states the retraction resulted from concerns that arose about the methodology of the study and the integrity and availability of the data. The authors provided a full response to the queries; however, the publisher determined the validity of the findings remained in question, the notice states. It continues:

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Data lost in a flood? The excuse checks out.

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When two recent retraction notices mentioned data were “destroyed in a flood,” we were skeptical. We’ve seen water take the blame for missing data before. 

In 2019, we wrote about a chemical engineer who said his suspicious data were lost in a laboratory flooding accident. The researcher lost nine papers as a result, as we previously covered. Three years earlier in 2016, researchers in Sri Lanka lost a paper after claiming they, too, had lost their data in a flood. We couldn’t verify the researchers’ claims.

But this time, thanks to a public records request, we’ve confirmed there was in fact a deluge at the researcher’s lab.

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‘Anyone can do this’: Sleuths publish a toolkit for post-publication review

For years, sleuths – whose names our readers are likely familiar with – have been diligently flagging issues with the scientific literature. More than a dozen of these specialists have teamed up to create a set of guides to teach others their trade.

The Collection of Open Science Integrity Guides (COSIG) aims to make “post-publication peer review” more accessible, according to the preprint made available online today. The 25 guides so far range from general – “PubPeer commenting best practices” – to field-specific – like spotting issues with X-ray diffraction patterns.

Although 15 sleuths are named as contributors on the project, those we talked to emphasized the project should be largely credited to Reese Richardson, the author of the preprint.

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