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Operational Range Bounding in Spectroscopy: A Safety Cage Framework for Machine Learning Models
Ensuring the reliability of black-box machine learning models in safety-critical space missions remains a significant challenge, particularly when ground-truth is unavailable for validation. Although machine learning models offer a powerful means to augment standard pipelines by extracting transmiss
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