AI peer reviewers unleashed to ease publishing grind

AI peer reviewers unleashed to ease publishing grind, in Nature, on the 22nd of November 2018
►https://www.nature.com/articles/d41586-018-07245-9

“If you build a decision-making system based on the articles which your journal has accepted in the past, it will have in-built biases,”

Peer Review: The Worst Way to Judge Research, Except for All the Others - The New York Times
▻https://www.nytimes.com/2018/11/05/upshot/peer-review-the-worst-way-to-judge-research-except-for-all-the-others.html

https://static01.nyt.com/images/2018/11/02/upshot/00up-final-crop-peer/00up-final-crop-peer-facebookJumbo.jpg

A 1982 paper describes a study in which two researchers selected 12 articles already accepted by highly regarded journals, swapped the real names and academic affiliations for false ones, and resubmitted the identical material to the same journals that had already accepted them in the previous 18 to 32 months. Only 8 percent of editors or reviewers noticed the duplication, and three papers were detected and pulled. Of the nine papers that continued through the review process, eight were turned down, with 89 percent of reviewers recommending rejection.

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