 This version of Bayes’ Theorem includes a term that represents the ratio of the likelihood of the experimental conditions on the hypothesis and background information (and auxiliaries) to the “likelihood” of the experimental conditions on the background (and auxiliaries) alone:  \(P_{\alpha}[c \pmid  h_i\cdot b]/ P_{\alpha}[c \pmid  b]\).  Arguably the value of this term should be 1, or very nearly 1, since the truth of the hypothesis at issue should not significantly affect how likely it is that the experimental conditions are satisfied. If various alternative hypotheses assign significantly different likelihoods to the experimental conditions themselves, then such conditions should more properly be included as part of the evidential outcome \(e\).