The presented results clearly demonstrate the superiority of tensorial learning. At a closer look, they especially reveal that scalar learning struggles with predicting the orientation of the tensor as expressed by the two angles θ and ϕ. Admittedly, this seems generally a harder task as compared to the tensor magnitude and shape, as the tensorial learning also exhibits a worse performance for the angles than for CQ and η. Nevertheless, the scalar learning is not even able to qualitatively capture the bimodal value distribution of θ and ϕ across the Li test set in the LTO-EFG database, cf. Fig. . This bimodality in θ and ϕ is even more pronounced for the The limitations of scalar learning with respect to capturing the tensor orientation imply that it will be particularly poor for any NMR observable sensitive to this orientation. It thereby does not matter if the tensor orientation is actually explicitly learned as through the scalar performance metrics (of θ and ϕ) introduced above or only implicitly contained in the observable (such as ω Q )