Building on the initial ablation study to evaluate the impact of various MIST features (pairwise neutral loss, MAGMa 8 substructure annotation, data augmentation, and unfolding) on fingerprint prediction accuracy, we extended this analysis to the database retrieval level. Fingerprint prediction is only an intermediate step during database annotation, and as previously reported, 2 improvements during this step might not necessarily correlate with enhanced performance on the full task. Given that certain features of MIST introduce considerable algorithmic complexity with only marginal improvements in fingerprint prediction accuracy, we sought to understand how this translates to changes in performance during database retrieval.