The AMS prospective stage uses two models: the best performing model from the model selection stage (an RF-C model) and the Similarity Baseline. Both models are retrained on all 10 folds and then used to predict scores on the AMS library, which contains 8,187,682 compounds after removing compounds that are also in the training data. First, the RF-C and Similarity Baseline models each select the top 1,500 ranked compounds based on their prediction scores. This produces two lists with many compounds present in both lists.