claim: The interesting point is that it also seems each time they come across a new  dataset it is simply replaced.
evidence: The goal of cross-validation is to test the model's ability to predict new data that was not used in estimating it, in order to flag problems like overfitting or selection bias and to give an insight on how the model will generalize to an independent dataset ( i.e., an unknown dataset, for instance from a real problem ).