Detection of plagiarism among rhinology scientific journals.

Ezer H BenaimSaima WaseSaif ZaidiAurelia MonkCristine Klatt-CromwellBrian D ThorpCharles S EbertAdam J Kimple Brent A Senior

Published in: International forum of allergy & rhinology (2024)

Automated plagiarism-checking software can be a valuable tool for detecting plagiarism in manuscripts. Twenty-five of 60 articles (42%) had at least one incidence of plagiarism, predominately text recycling. A "similarity score" ranging from 22% to 35% could be a potential cut-off value when screening submitted manuscripts.

Keyphrases

machine learning
risk factors
deep learning
high throughput
label free
single cell
quantum dots
sensitive detection