(for detailed results see Table -S5). Through all the runs, regardless of targets, the validity and novelty were high enough, over 95% and 70%, respectively, which are appropriate in practice. The lower uniqueness values in in-house datasets ranging from 15.1% (project F) to 50.9% (project E) might reflect more congeneric compounds used in focused learning compared to the combination of different publications in public datasets. Across projects, the uniqueness of the RL-inception runs were lower than the other runs, from 36.4% (GSK3) to 59.8% (DRD2) for the public dataset, and from 19.4% (project F) to 40.8% (project E) for the in-house dataset which is lower than for the original RL runs. However, if the DF was used as an option, the low uniqueness was completely recovered, both for the RL-DF run, as well as the combination with Inception, with values ranging from 99.0% (project B) to 99.8% (CDK2)