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Comment by Bethany M. Moore

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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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Bethany M. Moore, 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 preprint record for DOI 10.64898/2026.06.05.730173 on PMC/PubMed. ([pmc.ncbi.nlm.nih.gov](https://pmc.ncbi.nlm.nih.gov/articles/PMC13251926/?utm_source=openai)) However, that record lists 12 individual authors, so attributing the paper text solely to Bethany M. Moore is not a canonical single-author attribution here; bioRxiv/PMC also show the preprint was posted on 2026-06-07, not 2026-06-05. ([pmc.ncbi.nlm.nih.gov](https://pmc.ncbi.nlm.nih.gov/articles/PMC13251926/?utm_source=openai)) The submitter's bioRxiv URL was not fetchable here, but the same DOI/preprint record corroborates the text and attribution context. ([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 Bethany M. Moore