The researchers using AI to analyse peer review

被引：3
作者：
Van Noorden, Richard
机构：
来源：
NATURE | 2022年 / 609卷 / 7927期
关键词：
Publishing; Peer review;
D O I：
10.1038/d41586-022-02787-5
中图分类号：
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号：
07 ; 0710 ; 09 ;
摘要：
Anna Severin explains how her team used machine learning to try to assess the quality of thousands of reviewers’ reports.
引用
收藏
页码：455 / 455
页数：1
相关论文
共 6 条
[1]   Large-scale language analysis of peer review reports [J].
Buljan, Ivan ;
Garcia-Costa, Daniel ;
Grimaldo, Francisco ;
Squazzoni, Flaminio ;
Marusic, Ana .
ELIFE, 2020, 9 :1-10
[2]  
Eve M P., 2021, Reading Peer Review: PLOS ONE and Institutional Change in Academia
[3]  
Severin, 2022, PREPRINT
[4]   Peer review and gender bias: A study on 145 scholarly journals [J].
Squazzoni, Flaminio ;
Bravo, Giangiacomo ;
Farjam, Mike ;
Marusic, Ana ;
Mehmani, Bahar ;
Willis, Michael ;
Birukou, Aliaksandr ;
Dondio, Pierpaolo ;
Grimaldo, Francisco .
SCIENCE ADVANCES, 2021, 7 (02)
[5]   Development of ARCADIA: a tool for assessing the quality of peer-review reports in biomedical research [J].
Superchi, Cecilia ;
Hren, Darko ;
Blanco, David ;
Rius, Roser ;
Recchioni, Alessandro ;
Boutron, Isabelle ;
Gonzalez, Jose Antonio .
BMJ OPEN, 2020, 10 (06)
[6]   Development of the Review Quality Instrument (RQI) for assessing peer reviews of manuscripts [J].
van Rooyen, S ;
Black, N ;
Godlee, F .
JOURNAL OF CLINICAL EPIDEMIOLOGY, 1999, 52 (07) :625-629
1