Before revision:  The most transferable model is chosen with a cross-validation strategy that allows to automatically optimize the relative importance of heterogenous input datasets. The model architecture enlightens the structural information content of SHAPE reactivities and their dependence on local conformational ensembles. By using the selected model , we obtain enhanced populations for reference native structures and more sensitive and precise predicted structures in an independent validation set not seen during training .
After revision:  The most transferable model is chosen with a cross-validation strategy that estimates the performance of models on systems on which they are not trained. With the selected model , we obtain enhanced populations for reference native structures and more sensitive and precise predicted structures in an independent validation set not seen during training .