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IOP Publishing’s new tool to detect duplicate peer reviews

Push against reviewer fraud  

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IOP
First duplicate peer review detection tool to weed out reviewer fraud

IOP Publishing (IOPP) says it has developed a machine-learning-powered tool to help detect duplicate peer review reports, addressing a growing threat to research integrity in scholarly publishing.  

Duplicate peer reviews (where the same reviewer report is sent for multiple submissions) are problematic because they fail to provide a unique and critical assessment of a manuscript, making the peer review unreliable. The most egregious examples of this are “review mills”, organisations churning out fake reviews, often to inflate citations for a paying customer.  

Until now, such patterns in reviewer reports have been difficult to identify, limiting publishers’ ability to take timely action. The Duplicate Review Checker (DRC) changes this by automatically flagging duplicate review activity immediately and directly to editorial teams, enabling early interventions to safeguard the integrity of peer review. 

Since its pilot in 2024, the tool has processed around half a million reviewer reports dating back to 2020, identifying nearly 2,500 cases where more than 60% of the content closely matched other reviews. These included instances in which reports were reused across multiple manuscripts or submitted under different reviewer names. The tool is now integrated into IOPP’s internal publication workflow and used on all IOPP’s proprietary journals and some partner journals, keeping all reviewer data and reports confidential. 

To ensure the peer review process remains fair for both authors and reviewers, any duplicate report submitted is flagged for investigation to IOPP’s Research Integrity team. In these cases, the duplicate report is discarded and new reviewers are appointed to provide an independent and unbiased assessment of the manuscript. 

Supporting cross‑sector collaboration, IOPP will openly share insights into how the tool was developed with other publishers seeking to build similar solutions adapted to their own workflows.

Expanding the detection of duplicate reviews across the sector is a powerful way to disrupt review‑mill models and strengthen research integrity. This open approach reflects IOPP’s ongoing promise, as part of the Purpose-Led Publishing coalition, to publish only the content that genuinely adds to scientific knowledge and to prioritise purpose over profit. 

Kim Eggleton, head of peer review and research integrity at IOPP, said in a press release, “This tool is a powerful addition to our efforts to defend high peer review standards and weed out bad actors who try to manipulate the peer review process. It reflects our commitment to tackling unethical reviewing practices head-on and reinforces our role as a trusted, transparent and responsible publisher.”

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