Ranking actives according to their PubChem activity score is used as a benchmark method for true positive detection, and all significance tests are done compared to the Score method. Similar to false positive precision, the true positive precision is displayed as relative precision, where the true positive rates were subtracted from the precision scores prior to plotting. The PubChem activity score method outperforms random sorting on average when looking at relative true positive precision in Figure ). Figure ) shows that the Score method actually outperforms all other methods on 5 out of 25 datasets, justifying its usage for HTS true positive detection. The influence functions behave very similarly to the false positive prediction results. Their computational time is also independent of true or false positive prediction, as the label of interest does not change the methodology of the influence approaches.