At the classification (prediction) step, the performance of the best individual model (highlighted in yellow in Table ) and the consensus model (highlighted in green in Table ) was assessed based on their distance-to-model, which serves as an estimation of the applicability domain of the models. Since all models were constructed using the Morgan Chiral of radius 2 (2048-bits) fingerprint and various physicochemical properties, the distance-to-model was evaluated separately for each representation. Descriptive statistics of both distances for each target are detailed in Table . Compound's predictions were categorized into four quartiles based on their mean Jaccard or Euclidean distance from the compounds in the retraining set (see Methods Section 2.8 for further details). Table summarizes the distribution of predicted compounds across these quartiles, as well as those falling out of the defined applicability domain, using the Morgan Chiral of radius 2 (2048-bits) fingerprint. Similarly, Table presents the distribution of compounds using their corresponding preserved drug-like descriptors. The analyses in Tables and provides insight into how well the models generalize to novel compounds and highlights compounds lying beyond the applicability domain, which could serve as candidates for further experimental validation or re-evaluation of the models' chemical space coverage. Compounds on quartile 1 (Q1) should be prioritized for further analysis, including biological testing. In general, fewer compounds are considered "Out" when the distance is calculated with physicochemical properties. This could be due to the preservation of drug-like properties for the commercial and focused libraries, and the ChEMBL compounds, as observed in Section 3.3.1. The results for IBV Neuraminidase had the greatest number of compounds labeled as "Out" for both distances. This is aligned with the MODI results, since IBV Neuraminidase was the target with the lowest value for fingerprints.