Next, we retrained MIST's various components as outlined in the original study: the fingerprint prediction model, a baseline feed-forward neural network model, the contrastive model for embedding generation, and the forward model for simulating MS/MS data. In addition to public data from GNPS and MoNA, the primary MIST model was also trained on proprietary data from the commercial NIST20 spectral library. As this model is not publicly available, instead we utilized only data coming from public sources to retrain the models. While weights for the fingerprint prediction model and the contrastive model corresponding to the public data subset have also been provided on Zenodo by Goldman et al. [2], the baseline and simulation model were not provided.