Another factor affecting the search algorithm is of course the capability of the one-step retrosynthesis model. We have previously released a model trained on the entirety of the USPTO dataset , but this model was trained on reactions found in the reference routes, making it biased. Using this model in the search, or indeed any one-step model trained on the reactions in the reference routes will be a mix of neural network recommendations and what amounts to literature-lookup. However, we can train a new one-step model on the data that is not found in the reference routes, and because we left out three reactions per reaction template before extracting the routes, we have sufficient data to train a templatebased one-step model. In Section 4, we will detail the training of such a model. If someone wants to extract another set of templates or train a template-free one-step model, one can always perform such modeling as well on the provided data.