On MF-PCBA-37, no correlation is observed between the ∆R 2 and the SD/DR correlation, for all 3 machine learning algorithms when augmenting with SD labels (Figures ) and when augmenting with SD embeddings (Supplementary Figures ). However, on MF-PCBA-60 a moderate positive relationship is still present (Figures 3d to 3f, Supplementary Figures ). Interestingly, this indicates that the level of SD/DR correlation is not always indicative of the performance uplift, as some of the highest gains seen on MF-PCBA-37 were for datasets with extremely low correlation (e.g. AID434942 -AID2247, AID434937 -AID2237). Multiple linear regression models did not indicate significant contributions from any other dataset attribute other than the SD/DR correlation, such as the number of DR compounds or the number of SD compounds for MF-PCBA-60 (Supplementary Tables ).