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 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 is real and appears verbatim in the abstract for the preprint with DOI 10.64898/2026.06.05.730173 in PubMed/PMC records, but that preprint has multiple listed individual authors (including Aviral Bal) and does not attribute the wording to Aviral Bal alone, so this platform cannot verify it as a single-author quote. The submitter-provided passage is only a bibliographic note and does not itself contain the quoted sentence. bioRxiv listings also show the preprint was posted on 2026-06-07, not 2026-06-05. ([pubmed.ncbi.nlm.nih.gov](https://pubmed.ncbi.nlm.nih.gov/42282768/?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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