An atlas of biomedical literature furnishes a "bird's-eye" map of the relationships among nearly 21 million English-language research papers, which "should prove quite useful in looking at high-level trends," according to Kevin Boyack at research consulting company SciTech Strategies.
Researchers at Germany's University of Tübingen (TU) and information cartography company Nomic AI downloaded abstracts of the articles from the PubMed search engine, then sorted them by similarity using the PubMedBERT artificial intelligence (AI) large language model.
The model clustered similar publications into color-coded "neighborhoods," and then the researchers explored trends such as gender gap variation across the literature. They also underscored nearly 12,000 papers labeled as retracted on PubMed that often formed "islands."
TU's Dmitry Kobak suggested this approach could help identify other papers suspected of fabrication.
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