The magnetic classification task is less common for property prediction tasks as noted by its absence from MatBench . The boost in performance from considering ionic representations possibly arises from how magnetism arises from the electronic structure of a material through the spins of unpaired electrons centred on atomic sites. The oxidation states of the ions implicitly encode whether particular ions may possess paired or unpaired electrons depending on the crystal environments and species that they co-occurred within during the original training of the distributed representations which could explain the difference in performance between the SkipSpecies and SkipAtom representations.