Operational Range Bounding in Spectroscopy: A Safety Cage Framework for Machine Learning Models
This study evaluates a modular safety cage architecture that operates as a parallel monitoring layer to assess the validity of a prediction without modifying the underlying estimator, and identifies configurations that maximise risk-ranking accuracy and optimise the trade-off between data coverage and scientific perfor...