Improved source classification and performance analysis using Gaia DR3

The Discrete Source Classifier (DSC) provides probabilistic classification of sources in Gaia Data Release 3 using a Bayesian framework and a global prior. The DSC Combmod classifier in GDR3 achieved for the extragalactic classes (quasars and galaxies) a high completeness of 92 to contamination from the far larger star class. However, these single metrics mask significant variation in performance with magnitude and sky position. Furthermore, a better combination of the individual classifiers is possible. Here we compute two-dimensional representations of the completeness and the purity as function of Galactic latitude and source brightness, and exclude also the Magellanic Clouds where stellar contamination significantly depresses the purity. Reevaluated on a cleaner validation set and without introducing changes to the published GDR3 DSC probabilities themselves, we achieve for Combmod average 2-d completenesses of 92 89 proportions of extragalactic objects to stars in Gaia is expected to vary significantly with brightness and latitude, we introduce a new prior as a continuous function of brightness and latitude, and compute new class probabilities. This variable prior only improves the performance by a few percentage points, mostly at the faint end. Significant improvement, however, is obtained by a new additive combination of Specmod and Allosmod. This classifier, Combmod-α, achieves average 2-d completenesses of 82 93 respectively when using the global prior. Thus we achieve a significant improvement in purity for a small loss of completeness. The improvement is most significant for faint quasars where the purity rises from 20