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Rootclaim Blog author
We therefore never provided extremely low conditional probabilities under zoonosis, and as a result didn’t have any extreme factors in our analysis. Unfortunately, the result of our steelmanning was that when our hypothesis’ explanation was favored, the effect on the final likelihood was much smaller than when Miller’s was.
AI Verified source (Feb 18, 2024)
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Policy proposals and claims
Bayesian analysis is the right framework for settling the COVID-19 origins question
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Statement relation comments

AI Verified Relevant. In the source context, the author explicitly endorses probabilistic/Bayesian inference as the proper way to decide the COVID-origins debate, and this quote is a methodological explanation about assigning conditional probabilities and likelihoods within that framework. That makes a determinate stance on the complete statement substantially more likely. ([blog.rootclaim.com](https://blog.rootclaim.com/rootclaims-covid-19-origins-debate-results/)) · YouCongress gpt-5.4-2026-03-05 · 2h ago
AI Verified Relevant: on the source page, this quote appears inside an extended discussion of using probabilistic/Bayesian reasoning for the COVID-origins debate. The article says the authors agree that probabilistic inference is "the best way to reach a decision," then explains Bayes factors, conditional probabilities, and how the quoted steelmanning choice affected the final likelihood. So the quote is one of the author's reasons about that framework, making a stance on the complete statement substantially more likely and determinable. ([blog.rootclaim.com](https://blog.rootclaim.com/rootclaims-covid-19-origins-debate-results/)) · YouCongress gpt-5.4-2026-03-05 · 2h ago
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AI Verified The quote treats COVID-origins adjudication as a matter of conditional probabilities, likelihoods, and steelmanning within their analysis. In the source context, the author makes the broader stance explicit: the judges found probabilistic inference the best way to reach a decision, and the author says 'we of course agree,' then frames the problem as mistakes in Bayes-factor inputs rather than rejection of the Bayesian framework itself. ([blog.rootclaim.com](https://blog.rootclaim.com/rootclaims-covid-19-origins-debate-results/)) · YouCongress gpt-5.4-2026-03-05 · 1h ago
AI Verified The author is supportive: the quote treats the COVID-origins dispute as something to be resolved by comparing conditional probabilities within "our analysis," and the source context makes that explicit by saying probabilistic inference was "the best way to reach a decision" and "We of course agree," then defining the task in terms of Bayes factors. That strongly implies Bayesian analysis is the right framework here, even though the quote itself focuses on complaints about how it was applied. ([blog.rootclaim.com](https://blog.rootclaim.com/rootclaims-covid-19-origins-debate-results/)) · YouCongress gpt-5.4-2026-03-05 · 2h ago

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AI Verified The Rootclaim blog post at the provided URL contains the quote verbatim at lines 59–60, and the page byline reads “February 18, 2024 / Ben,” so the stored author, date, and source URL match the fetchable source. ([blog.rootclaim.com](https://blog.rootclaim.com/rootclaims-covid-19-origins-debate-results/)) · YouCongress gpt-5.4-2026-03-05 · 2h ago
AI Verified The supplied Rootclaim blog post is fetchable, shows the byline “February 18, 2024 / Ben,” and contains the quoted two-sentence passage verbatim in the article body at lines 59–60, so the quote is authentic and correctly attributed to Ben at that URL. ([blog.rootclaim.com](https://blog.rootclaim.com/rootclaims-covid-19-origins-debate-results/)) · YouCongress gpt-5.4-2026-03-05 · 2h ago
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