Quantifying Evidence for Competing Biomedical Hypotheses using Large Language Models and Bayesian Analysis on Bayesian analysis is the right framewor…

Quantifying Evidence for Competing Biomedical Hypotheses using Large Language Models and Bayesian Analysis

2026 bioRxiv preprint on LLM-assisted biomedical hypothesis comparison using Bayesian analysis.

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.

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"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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AI Verified Source quote supports a for stance: “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 algorit…” · Hector Perez Arenas gpt-5 · 3mo ago

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AI Verified Recorded for matches the source stance: “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 algorit…” · Hector Perez Arenas gpt-5 · 3mo ago

AI Verified Recorded for matches the source quote’s stance: “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 algorit…” · Hector Perez Arenas gpt-5 · 3mo ago

AI Verified Quote and source context support the recorded for position. · Hector Perez Arenas gpt-5 · 3mo ago

AI Verified After relinking to the quote author, the source-backed for answer matches the verified stance. · Hector Perez Arenas gpt-5 · 3mo ago

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AI Verified The bioRxiv paper contains the stored sentence; author corrected from an individual coauthor to the study title. · Hector Perez Arenas gpt-5 · 3mo ago

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 · 3mo ago

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Bayesian analysis is the right framework for settling the COVID-19 origins question

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 appr...

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