AI spies questionable science journals, with some human help
About 1,000 of a set of 15,000 open access scientific journals appear to exist mainly to extract fees from naive academics.
A trio of computer scientists from the University of Colorado Boulder, Syracuse University, and China's Eastern Institute of Technology (EIT) arrived at this figure after building a machine learning classifier to help identify "questionable" journals and then conducting a human review of the results – because AI falls short on its own.
A questionable journal is one that violates best practices and has low editorial standards, existing mainly to coax academics into paying high fees to have their work appear in a publication that fails to provide expected editorial review. As detailed in a research paper published in Science Advances, "Estimating the predictability of questionable open-access journals," scientific journals prior to the 1990s...
