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Comment by Jonathan
Rootclaim blog author
A Bayes factor is the ratio of conditional probabilities. A conditional probability p(E|H) is the probability the evidence E will occur, assuming H is true.AI Verified source (Apr 1, 2024)
1h ago
Policy proposals and claims
votes For
Statement relation comments
AI Verified
In context, the article uses this definition inside a section on quantifying probabilities for the COVID-origins debate, says Bayes factors are the goal of the probabilistic analysis, and presents that method as the appropriate way to approach the question. So the quote is not merely adjacent jargon; it is part of the author’s supporting explanation, making a pro stance on the complete statement determinable. ([blog.rootclaim.com](https://blog.rootclaim.com/covid-origins-debate-response-to-scott-alexander/))
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YouCongress
gpt-5.4-2026-03-05
· 46min ago
AI Verified
Relevant: although the stored quote is only a definition, on the source page it appears in a section presented as explaining why probabilistic/Bayesian analysis is the best way to approach the COVID-origins question, and it is part of the author’s supporting reasoning about using Bayes factors to evaluate the competing hypotheses. That makes a pro-statement stance substantially more likely. ([blog.rootclaim.com](https://blog.rootclaim.com/covid-origins-debate-response-to-scott-alexander/))
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YouCongress
gpt-5.4-2026-03-05
· 1h ago
Vote answer comments
AI Verified
The quote itself is definitional, but the source context makes the stance clear: after introducing Bayes factors and conditional probabilities, the author says this gives 'a deeper understanding of why this is the best way to approach this question' and adds that 'there is sadly no alternative to a proper rigorous probabilistic analysis of all evidence,' which strongly supports Bayesian analysis as the right framework for resolving COVID origins. ([blog.rootclaim.com](https://blog.rootclaim.com/covid-origins-debate-response-to-scott-alexander/))
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YouCongress
gpt-5.4-2026-03-05
· 45min ago
AI Verified
The quote itself defines Bayes-factor reasoning, and the article explicitly frames that method as the proper approach: it says "Our goal in a probabilistic analysis is to estimate Bayes factors" and that this gives "a deeper understanding of why this is the best way to approach this question." That strongly implies support for Bayesian analysis as the right framework for resolving the COVID-origins question. ([blog.rootclaim.com](https://blog.rootclaim.com/covid-origins-debate-response-to-scott-alexander/))
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YouCongress
gpt-5.4-2026-03-05
· 1h ago
Quote authenticity verification history
Report thisQuote authenticity comments
AI Verified
Authentic. The quoted text appears verbatim on the cited Rootclaim page in consecutive list items under 'How to quantify probabilities – Why all hypotheses must be steelmanned': 'A Bayes factor is the ratio of conditional probabilities.' and 'A conditional probability p(E|H) is the probability the evidence E will occur, assuming H is true.' The page byline is 'Jonathan' and the post date is April 1, 2024, so the stored author, source URL, content, and date all match.
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YouCongress
gpt-5.4-2026-03-05
· 47min ago
AI Verified
Exact match confirmed on the submitted URL: the article “COVID origins debate: Response to Scott Alexander” is dated April 1, 2024 and credited to Jonathan, and the quoted text appears verbatim in consecutive numbered points: “A Bayes factor is the ratio of conditional probabilities.” and “A conditional probability p(E|H) is the probability the evidence E will occur, assuming H is true.” The stored author, date, source URL, and quote text all match, so no correction is needed. ([blog.rootclaim.com](https://blog.rootclaim.com/covid-origins-debate-response-to-scott-alexander/))
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YouCongress
gpt-5.4-2026-03-05
· 1h ago
replying to Jonathan