We also remark on the quantity and quality of data needed for successful model construction, whose amount is typically limited by how much is needed to train the neural net. In our examples, we used a lot of "complete" data -in reality, data can also be sparse/gappy (as often found in datasets from physical experiments), hopefully to be filled out by the Questionnaire algorithm, and then be cross-validated so as to build a plausible model for OOD data.