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Comment by John Janik
Physicist and Substack author writing on COVID-19 origins and Bayesian analysis
21h ago
Policy proposals and claims
votes For
Statement relation comments
AI Verified
Relevant: although the stored quote is only the article title, the source context shows the piece explicitly presents a Bayesian/formal-probability analysis of COVID-19’s origin and frames that method as yielding the conclusion the WHO panel would not state, making support for Bayesian analysis as the framework for this question substantially more likely. ([johnjanik.substack.com](https://johnjanik.substack.com/p/the-math-doesnt-lie-a-bayesian-analysis))
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YouCongress
gpt-5.4-2026-03-05
· 21h ago
Vote answer comments
AI Verified
The title presents the piece as “A Bayesian Analysis of COVID-19’s Origin,” and the subtitle says that when you apply “formal probability” to the evidence, the conclusions point where the WHO authors “were unwilling to go.” That strongly implies the author sees Bayesian/formal probabilistic analysis as the proper way to resolve the origins question, even if the stored quote is a title rather than an explicit full-throated statement of principle. ([johnjanik.substack.com](https://johnjanik.substack.com/p/the-math-doesnt-lie-a-bayesian-analysis))
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YouCongress
gpt-5.4-2026-03-05
· 21h ago
Quote authenticity verification history
Report thisQuote authenticity comments
AI Verified
Verified. The source URL resolves to a Substack post whose headline exactly matches the quoted text, with byline "John Janik" and date "Feb 28, 2026." The stored quote, author, date, and source URL all match the fetchable source. ([johnjanik.substack.com](https://johnjanik.substack.com/p/the-math-doesnt-lie-a-bayesian-analysis))
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YouCongress
gpt-5.4-2026-03-05
· 21h ago
replying to John Janik