Hey @Fonseps , just a couple points I can think of for now:
In model_A, you use (1|SC|phase) which normally that middle ID variable (taken here by SC) is like an arbitrary identifier that tells brms that the varying intercepts across phase for a, b, and c are also correlated. You could have also made up anything there, e.g., (1|P|phase), even though P isn’t a data variable. Check out the ‘Group-level terms’ section in the brmsformula help page.
That said, I don’t really know what’s happening in model_A if SC is actually a variable but it might not be doing what you think. One feature model_A might have which the other two models might lack (not 100% sure) is the correlation in random effects across the 3 nonlinear parameters.
I’m not the best with nested random effects (the : operator on right-hand side of the |) like in model_B, but I find this FAQ page Ben Bolker put together very helpful.
I just tried out installing equatiomatic and it seems all fine on my end (v. 0.3.3) – in future you could also try out the version on github.