In a recent publication in the journal Scientometrics, a team of researchers led by Lutz Bornmann (Scopus h-index=64), the esteemed recipient of the 2019 Derek John de Solla Price Medal, demonstrates that ChatGPT provides a low-cost alternative for identifying disruptive academic papers. However, the authors emphasize a crucial caveat: "it should only be used by someone who can assess the quality of its replies" https://link.springer.com/article/10.1007/s11192-024-05176-z
In a related context, Clarivate Analytics, has long employed a methodology that leverages highly cited papers to forecast future Nobel Laureates. To date, this approach has been remarkably successful, with 75 accurate predictions of Nobel Prize winners. In the 2024 Nobel Prize announcements, this methodology proved its efficacy once again by predicting 8 (eight) additional laureates. Two in Medicine (V. Ambros and G. Ruvkun), three in Chemistry (D. Hassabis, D. Baker, and J. Jumper), and three in Economics (D. Acemoglu, S. Johnson, and J. Robinson).
PS - Citations serve not only as a measure of academic impact but also as a tool for distinguishing those who genuinely contribute to the scientific community from those who may hold academic titles without true merit. In many instances, such titles may have been acquired through questionable or corrupt practices, further undermining the integrity of the academic system. https://19-pacheco-torgal-19.blogspot.com/2024/07/how-scientific-community-can-identify.html
