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Journal Impact Factor and Peer Review Thoroughness and Helpfulness: A Supervised Machine Learning Study. (arXiv:2207.09821v1 [cs.DL])
July 21, 2022, 1:10 a.m. | Anna Severin, Michaela Strinzel, Matthias Egger, Tiago Barros, Alexander Sokolov, Julia Vilstrup Mouatt, Stefan Müller
cs.LG updates on arXiv.org arxiv.org
The journal impact factor (JIF) is often equated with journal quality and the
quality of the peer review of the papers submitted to the journal. We examined
the association between the content of peer review and JIF by analysing 10,000
peer review reports submitted to 1,644 medical and life sciences journals. Two
researchers hand-coded a random sample of 2,000 sentences. We then trained
machine learning models to classify all 187,240 sentences as contributing or
not contributing to content categories. We …
arxiv dl impact learning machine machine learning peer review study supervised machine learning
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