Peer review analyze: A novel benchmark resource for computational analysis of peer reviews
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DOI: 10.1371/journal.pone.0259238
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References listed on IDEAS
- Giangiacomo Bravo & Francisco Grimaldo & Emilia López-Iñesta & Bahar Mehmani & Flaminio Squazzoni, 2019. "The effect of publishing peer review reports on referee behavior in five scholarly journals," Nature Communications, Nature, vol. 10(1), pages 1-8, December.
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- Elise S. Brezis & Aliaksandr Birukou, 2019. "Arbitrariness in the Peer Review Process," Working Papers 2019-08, Bar-Ilan University, Department of Economics.
- Carole J. Lee & Cassidy R. Sugimoto & Guo Zhang & Blaise Cronin, 2013. "Bias in peer review," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 64(1), pages 2-17, January.
- Heidi Ledford & Richard Van Noorden, 2020. "High-profile coronavirus retractions raise concerns about data oversight," Nature, Nature, vol. 582(7811), pages 160-160, June.
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Cited by:
- Buljan, Ivan & Garcia-Costa, Daniel & Grimaldo, Francisco & Klein, Richard A. & Bakker, Marjan & Marušić, Ana, 2024. "Development and application of a comprehensive glossary for the identification of statistical and methodological concepts in peer review reports," Journal of Informetrics, Elsevier, vol. 18(3).
- Wenqing Wu & Haixu Xi & Chengzhi Zhang, 2024. "Are the confidence scores of reviewers consistent with the review content? Evidence from top conference proceedings in AI," Scientometrics, Springer;Akadémiai Kiadó, vol. 129(7), pages 4109-4135, July.
- Gabriel Okasa & Alberto de Le'on & Michaela Strinzel & Anne Jorstad & Katrin Milzow & Matthias Egger & Stefan Muller, 2024. "A Supervised Machine Learning Approach for Assessing Grant Peer Review Reports," Papers 2411.16662, arXiv.org, revised Dec 2024.
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