Before revision:  Notably, it  can leverage the learned chemical insights, e.g. by predicting unknown spin states or by properly modeling physical limits. Moreover, it is able to generalize across chemical and conformational space and thus close an important remaining gap for today's machine learning models in quantum chemistry.
After revision:  Notably, it can leverage the learned chemical insights, e.g. by predicting unknown spin states , thus helping to close a further important remaining gap for today's machine learning models in quantum chemistry.