This article gives a conceptual review of the e-value, ev(H|X) -- the epistemic value of hypothesis H given observations X. This statistical significance measure was developed in order to allow logically coherent and consistent tests of hypotheses, including sharp or precise hypotheses, via the Full Bayesian Significance Test (FBST). Arguments of analysis allow a full characterization of this statistical test by its logical or compositional properties, showing a mutual complementarity between results of mathematical statistics and the logical desiderata lying at the foundations of this theory.

翻译：本文对e值——即给定观测数据X时假设H的认知价值ev(H|X)——进行概念性综述。该统计显著性测度的提出，旨在通过完全贝叶斯显著性检验（FBST）实现对假设（包括尖锐或精确假设）的逻辑自洽且一致的检验。分析论证表明，可通过其逻辑或组合特性完整刻画该统计检验方法，从而揭示数理统计结果与该理论奠基性逻辑诉求之间的相互补充关系。