Published on in Vol 25 (2023)
Preprints (earlier versions) of this paper are
available at
https://preprints.jmir.org/preprint/42789, first published
.
![Evaluating the Ability of Open-Source Artificial Intelligence to Predict Accepting-Journal Impact Factor and Eigenfactor Score Using Academic Article Abstracts: Cross-sectional Machine Learning Analysis Evaluating the Ability of Open-Source Artificial Intelligence to Predict Accepting-Journal Impact Factor and Eigenfactor Score Using Academic Article Abstracts: Cross-sectional Machine Learning Analysis](https://asset.jmir.pub/assets/8dcfbe702fd5a7d780eb6ee5ce956e1c.png 480w,https://asset.jmir.pub/assets/8dcfbe702fd5a7d780eb6ee5ce956e1c.png 960w,https://asset.jmir.pub/assets/8dcfbe702fd5a7d780eb6ee5ce956e1c.png 1920w,https://asset.jmir.pub/assets/8dcfbe702fd5a7d780eb6ee5ce956e1c.png 2500w)
There are no citations yet available for this article according to Crossref .