Photometric classification of dusty stars in the Magellanic Clouds is reliable for abundant classes with distinct signatures but fails for rare or overlapping classes, according to a model trained on spectroscopic labels.
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Comparison of Photometric and Spectroscopic Labels in Classifying Dusty Stellar Sources Using Machine Learning in the Magellanic Clouds
Photometric classification of dusty stars in the Magellanic Clouds is reliable for abundant classes with distinct signatures but fails for rare or overlapping classes, according to a model trained on spectroscopic labels.