(iii) the regioSQM prediction. We also find that using GNN predicted shifts gives similar performance in Just as every model has limitations, the framework we present in this work still leaves room for improvement. We mention that the accuracy of the model depends on the quality of 3D structures generated by MMFF to some extent. We have found several examples where the poor MMFF structure leads to a discrepancy in prediction, for instance, ketenimines. Thus, the model is likely to improve further with more robust empirical or semi-empirical structures, along with associated relative energies that are used to carry out Boltzmann averaging, such as those from xTB. Other potential improvements will include extending the model to biomolecules, coupling constant prediction, and the adoption of probability metrics such as DP4 for structure elucidation.