Earlier quoted context omitted.
It has probably been a mistake to have so many articles that are effectively "We measured A and its value suggests the following theory" rather than "To test theory B we measured A and found it did(n't) agree" I reckon that lack of a good theory is the by far best predictor for non-replicable results.
I think there are several issues with this. In these fields, theories (not so fundamental ones) may not be very useful, in contrast with fields like Mathematics or Physics where a hypothesis may lead to a lot of other theoretical results. For example, if material A has property X, there will be a lot of applications for it, but this hypothesis cannot be used as a foundation for other theoretical research. As a result…
Medical research in particular seems to suffer a lot from papers where something has been measured with no supporting theory whatsoever and consequently no real information other than "If you do what we did you probably get the same result". Rather unsurprisingly this is hard to replicate because there's no theory telling you what is and isn't relevant to replicate.
I'm not saying this is easy to fix, but maybe we should focus more effort on papers that expand the theory, rather than papers that at best show that something might be the case but we don't know why.