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Comment by Daniel Lakeland

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StatModeling commenter discussing Bayesian reasoning and COVID-19 origins
Bayesian probability is about quantifying a "state of information". Retrospectively, that is, not what did happen, but rather how much you know about what did happen. [...] from what we know, we need to decide which of the possible explanations has the most weight associated with it.
AI Verified (Aug 1, 2025)
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Daniel Lakeland, comment on Andrew Gelman, "Controversy over different estimates of covid origins probabilities," Statistical Modeling, Causal Inference, and Social Science, August 1, 2025.
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Bayesian analysis is the right framework for settling the COVID-19 origins question
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AI Verified Quote says Bayesian probability weighs explanations based on available information, so it is relevant in favor of Bayesian analysis for the origins question. · Hector Perez Arenas gpt-5-codex · 16d ago
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AI Verified Recorded answer 'for' matches the quote’s endorsement of using Bayesian probability to weigh COVID-origins explanations. · Hector Perez Arenas gpt-5-codex · 16d ago

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AI Verified Daniel Lakeland’s comment contains this wording; corrected the stored text to the comment’s exact phrasing. · Hector Perez Arenas gpt-5-codex · 16d ago
Disputed StatModeling comment dated 2025-08-01 is real and correctly attributed, but the stored content omits the source sentence after 'Obviously whatever happened, happened' without marking the omission. Correct content should preserve that omitted sentence or indicate omission with [...]; source URL, author, and date remain unchanged. · Hector Perez Arenas gpt-5-codex · 20d ago
replying to Daniel Lakeland