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Comment by Jonathan
Rootclaim blog author
Note that these are just the three methods we identified. To continue to believe the extreme p=1/10000 or p=1/000, you also need to be very confident there aren’t other explanations that were not yet identified. More generally, such extreme numbers are not possible outside very controlled environments where all confounders can be reliably eliminated (more on this below).AI Verified source (Apr 1, 2024)
2h ago
Policy proposals and claims
votes For
Statement relation comments
AI Verified
In source context, this quote sits inside the article’s methodological section on estimating Bayes factors/conditional probabilities for COVID origins and is used as a reason against extreme likelihood claims unless confounders and alternative explanations are accounted for. That makes the author’s support for Bayesian/probabilistic analysis as the framework for this question substantially more likely, so the quote is relevant. ([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
· 2h ago
AI Verified
The quote is relevant because it directly discusses how conditional probabilities should be assigned in the COVID-origins debate and argues that extreme likelihood numbers are unjustified in this domain due to confounders and unknown alternative explanations. In the source context, Rootclaim presents this as part of its broader methodological argument about Bayes factors and probabilistic inference in evaluating COVID origins, so the author’s stance on whether Bayesian analysis is the right framework is substantially more determinable from this passage and its context. ([blog.rootclaim.com](https://blog.rootclaim.com/))
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YouCongress
gpt-5.4-2026-03-05
· 2h ago
Vote answer comments
AI Verified
The quote criticizes assigning extreme probabilities like "p=1/10000" in a complex, noisy case, but not Bayesian reasoning itself. In the source context, the author says the strength of evidence is measured by Bayes factors and that the goal of the analysis is to estimate those factors, so he is clearly treating Bayesian/probabilistic analysis as the proper framework for resolving the COVID-origins evidence, while stressing it must be applied carefully.
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YouCongress
gpt-5.4-2026-03-05
· 2h ago
AI Verified
For. The quote argues that settling the issue depends on estimating probabilities carefully and rejecting unjustified extreme likelihoods in a complex real-world case. In the same source context, the author explicitly says “our goal in a probabilistic analysis is to estimate Bayes factors” and presents that as “the best way to approach this question,” which strongly implies support for Bayesian analysis as the proper 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
· 2h ago
Quote authenticity verification history
Report thisQuote authenticity comments
AI Verified
Verified: the Rootclaim post “COVID origins debate: Response to Scott Alexander” is dated April 1, 2024 and credited to “Jonathan” in the page header, and the exact quoted text appears verbatim in the article at line 135 of the source URL. ([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
· 2h ago
AI Verified
The source URL is fetchable, and the Rootclaim post titled “COVID origins debate: Response to Scott Alexander” is dated April 1, 2024 and bylined “Jonathan.” The submitted passage appears there verbatim in the article body, so the quote is authentic, correctly attributed, and present at the cited URL. ([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
· 2h ago
replying to Jonathan