"Using embeddings + logistic classifier, the architecture matches or beats Jev and Laya in all basic classification"

Have I understood correctly that you trained only the logistic classifier, but didn't need to train the embedding model?

If so, I'm curious whether you compared that approach (A) with:

B) Jev only, with a single output.

C) Jev with multiple outputs fed into a logistic classifier.

Obviously C has cons (can't be self-hosted, needs some up-front work on deciding the shape of the output) but it might be somewhat more interpretable. (And I suppose it might have better performance?)