Paul Brookes is a biologist with a passion for sleuthing out fraud. Although he studies mitochondria at the University of Rochester, he also secretly ran a science-fraud.org, a site for people to post their concerns about papers. Following legal threats, he revealed he was the author and shut the site in 2013 — but didn’t stop the fight. Recently, he’s co-authored a paper that’s slightly outside his day job: Partnering with computer scientist Daniel Acunaat Syracuse University and computational biologist Konrad Kording at the University of Pennsylvania, they developed a software to help detect duplicated images. If it works, it would provide a much needed service to the research community, which has been clamoring for some version of this for years. So how did this paper — also described by Nature News — come about?
Image manipulation is one of the more common reasons for forced retractions/research misconduct so such a tool would be welcome for institutions/publishers/peer reviewers.
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Paul Brookes: I had authored a paper on the relationship between levels of internet publicity (blogs etc.) and actions taken against problematic papers in the biosciences – retractions, corrections, etc. As such, I was sitting on a large database (500+ papers) with documented image problems. Konrad and Daniel approached me by email, to request this set of examples, to act as a training set for their machine learning algorithm.
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