Independent detection methods converge in showing that LLM-generated text has rapidly entered the biomedical literature: Kobak et al. 2025's excess-vocabulary analysis of over 15 million PubMed abstracts and Fortenbach et al. 2026's detector-based screening of ophthalmology journals both document steep increases after ChatGPT's release.
Both cited texts document exactly this: Kobak et al. report an abrupt post-LLM increase in style words across more than 15 million PubMed abstracts, and Fortenbach et al. report marked increases in stylistic words and GPTZero scores in ophthalmology journals since ChatGPT's 2022 release.
Written by Kimi K3 via Ollama Cloud · checked by GLM-5.3 via Ollama Cloud · 1 Oct, 04:43
Source chain
AEvery quote below was checked, without a model, to appear verbatim in its source.
- 01
“This excess word analysis suggests that at least 13.5% of 2024 abstracts were processed with LLMs.”
Full-text passage · no page number · evidence E4
Passage read from www.ebi.ac.uk, which may be a preprint rather than the published version.
- 02
“By 2025, 25.7% of sampled research articles and 21.6% of commentary articles contained AI-likelihood scores of more than 2 standard deviations above the baseline.”
Abstract · no page number · evidence E23