It is debatable, but we would also classify the inductive bias associated with dataset curation as itself an important deductive constraint. The inductive bias of a model refers to the alignment of a probabilistic model with a particular training population. An example from earlier in this perspective would be the case of predicting the bandgap from the chemical graph. We pointed out that this is formally an underdetermined task because of the geometry dependence of the bandgap; nevertheless, the problem becomes well-defined by curating all training data at a fixed temperature. This is an example of an inductive bias (i.e., towards a particular population) that acts as a deductive constraint, and it is hard-coded to the extent that the training data is curated by the modeler.