Reading the paper it seems like a pretty accurate description. The paper just calls it a "private email" instead of a "non-institutional email". For example (@@

Reading the paper it seems like a pretty accurate description. The paper just calls it a "private email" instead of a "non-institutional email". For example (@@@ emphasis is mine): > To identify indicators able to red-flagged fake publications (RFPs), we sent questionnaires to authors. Based on author responses, three indicators were identified: @@@“author's private email”@@@, “international co-author” and “hospital affiliation”. > For Studies 1 to 6 we identified two easy-to-detect indicators, where a publication was labelled as RFP: @@@if an author used a private email@@@ and had no international partner. > Then we combined the two best indicators (@@@“author's private email”@@@ and “hospital affiliation”) to form a classification (tallying) rule: “If both indicators are present, classify as a potential fake, otherwise not” (the “AND” rule) (Katsikopoulos et al., 2020). Fun bonus there with the 2020 book citation for the concept of an AND gate in a classifier.