Seeking Critique on Research Approach to Open Set Recognition (Novelty Detection) [R]

Hey guys, I'm an independent researcher working on a project that tries to address a very specific failure mode in LLMs and embedding based classifiers: the inability of the system to reliably distinguish between "familiar data" that it's seen variations of and "novel noise." The project's core idea is moving from a single probability vector (P(class|input)) to a dual-output system that measures μ(x), a continuous familiarity score bounded [0,1], derived from set coverage axioms.