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Comment by Jack Freeman

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Researcher and coauthor of a 2026 preprint on Bayesian analysis for competing biomedical hypotheses
Here, we introduce KM-GPT-DCH, an algorithm that combines co-occurrence methods with large language models (LLMs) to develop a transparent and reproducible literature-based algorithm to compare controversial hypotheses using a structured scoring approach with Bayesian methods to estimate confidence.
Disputed (Jun 5, 2026)
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Jack Freeman, coauthor of "Quantifying Evidence for Competing Biomedical Hypotheses using Large Language Models and Bayesian Analysis," bioRxiv, June 5, 2026.
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Bayesian analysis is the right framework for settling the COVID-19 origins question
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Disputed The sentence appears verbatim in the abstract of the same preprint/DOI on PMC/PubMed, but the work is a multi-author preprint credited to Bethany M. Moore, Jack Freeman, Robert J. Millikin, Chitrasen Mohanty, Kevin Shine George, Aviral Bal, Cannon Lock, John-Demian Sauer, Megan E. Spurgeon, Darcie L. Moore, Brittany G. Travers, and Ron Stewart—not a sole-author Jack Freeman statement. bioRxiv’s archive entry for this DOI also shows the preprint was posted on 2026-06-07, so the stored 2026-06-05 date is not the canonical posting date. Because this platform cannot verify a many-author paper passage as a single-author quote, the attribution is disputed. ([pmc.ncbi.nlm.nih.gov](https://pmc.ncbi.nlm.nih.gov/articles/PMC13251926/?utm_source=openai)) · YouCongress gpt-5.4-2026-03-05 · 1h ago
replying to Jack Freeman