Why does the likelihood grow exactly twice? (I'm just used to really indirect evidence, which is also seldom binary in the sense that I only get to see whole suits of traits, which usually go together but in some obscure cases, vary in composition. So I guess I have plenty of C-bits that do go in B-bits that might go in A-bits, but how do I measure the change in likelihood of A given C? I know it has to do with d-separation, but if C is something directly observable, like biomass, and B is an abstraction, like species, should I not derive A (an even higher abstraction, like 'adaptiveness of spending early years in soil') from C? There are just so much more metrics for C than for B...) Sorry for the ramble, I just felt stupid enough to ask anyway. If you were distracted from answering the parent, please do.