When gauging the strength of a prediction, it's important to view the inside view in the context of the outside view. For example, most medical studies that claim 95% confidence aren't replicable, so one shouldn't take the 95% confidence figures at face value.

This implies that the average prior for a medical study is below 5%. Does he make that point in the book? Obviously you shouldn't use a 95% test when your prior is that low, but I don't think most experimenters actually know why a 95% confidence level is used.