We hypothesized that the failure of the first experiment could be due to the information gain from a random molecule in the CCV withheld set being to large. The idea is that since the withheld set contained only molecules that are distinct from the training set due to the clustering, selecting a molecule at random would still provide rich information to a learner as it had never before seen this type of molecule in its prior training. This could allow the relative performance of random selection the active learning approaches to be similar, since the randomly selected molecules are still providing meaningful information from which the model can learn.