We have unit tests that are running some underlying model. We provide it with some test input, and receive some outputs + floating point scores. What's a good practice from a unit-testing standpoint? Should we place assertions on the floating points themselves, or just check that they are within a good range (i.e. > 0.5)? I am on the side to test everything as precisely as possible, but I do understand that a small model change can break all the tests. Maybe reg-testing / monitoring is a better way to catch model-output changes?