The Bayesian perspective is based on conditioning related to reported evidence that is considered to be certain. What is called ‘Radical Probabilism’ replaces such an extreme view by introducing uncertainty on the reported evidence. How can such equivocal evidence be used in further inferences about a main hypothesis? The theoretical ground is introduced with the aim of offering to the readership an explanation for the generalization of the Bayes’ Theorem. This extension—that considers uncertainty related to the reporting of evidence—also has an impact on the assessment of the value of evidence through the Bayes’ factor. A generalization for such a logical measure of the evidence is also presented and justified.

中文翻译：

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连贯更新信念度：激进概率，贝叶斯定理的推广及其对证据评估的影响

贝叶斯观点基于与被认为是确定的报告证据相关的条件。所谓的“激进概率论”通过在报告的证据中引入不确定性来取代这种极端观点。这些模棱两可的证据如何用于对主要假设的进一步推论？引入理论基础的目的是为读者提供对贝叶斯定理推广的解释。这一扩展——考虑到与证据报告相关的不确定性——也通过贝叶斯因子对证据价值的评估产生影响。还提出并证明了对证据的这种逻辑测量的概括。