Signals from the community
Publication fraud is harming trust in research. To help protect the integrity of the scholarly record and restore trust in research many researchers and sleuths comb the literature to identify patterns and markers of fraud in research articles, and some build tools to enhance these efforts.
The Problematic Paper Screener, an academic project led by Guillaume Cabanac and collaborators, combines automatic machine detection and human evaluation to identify issues in publications, including the presence of tortured phrases.
We’re excited to announce the integration of articles flagged by the Problematic Paper Screener into the Signals Graph as a new signal. This includes over 12,000 problematic publications that have not been retracted. These problematic publications are cited more than 160,000 times by articles. This is now visible through Signals.
We aim to help sleuths, publishers, and researchers gain greater visibility of these problematic papers and enable them to uncover additional research integrity issues with Signals. Ultimately, this will help correct the scholarly record and prevent the publication of problematic articles.
Explore Signals by searching a DOI on our platform.
Want to raise awareness within the research community about integrity issues?
Contact us to add your own insight on problematic articles to the Signals Graph.
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