eLife Assessment
This work introduces FunC-ESMs, a proteome-scale framework to classify loss-of-function missense variants into distinct mechanistic groups by combining two complementary state-of-the-art machine learning models. The strength of evidence is convincing, supported by solid benchmarking, integration with experimental datasets, and careful methodological design. The significance of the findings is valuable, providing a resource of clear interest to researchers and diagnostic laboratories working on variant interpretation.