Training on building block P(active) values yields precise predictions for the activity of trisynthons. To determine how much signal P(active) value alone has in predicting the activity of a trisynthon, we design a simple test. We randomly split our total dataset into a training set containing 90% of the data and a test set with the remaining 10%, while ensuring that all building blocks in the training set are sampled in the test set. This means all the trisynthons in the test set are strictly new combinations of already tested building blocks, allowing us to evaluate whether P(active) can be used to predict the activity of trisynthons when the P(active) values for each building block can be calculated. In later sections, we tackle the issue of predicting the activity of trisynthons composed of untested building blocks.