The last block of values is not meant for the x-block in ML models. After the model is built, new compositions could be tested in the prediction of crystal structure classes or physical properties. While ML in general is not great at extrapolation to push the boundary to get the record-performing compound, it might be more helpful to see how the values of predicted compositions balance with sustainability of a compound. Abundance is used for indication of potential scarcity of elements for scaling up the production of a useful material predicted by ML. HHI index is an economic factor which helps to assess economic risks associated with proposing a novel material. The cost of a proposed compound might be another factor, and while the performance of the predicted compound might not be stellar, its affordability may play the key role. [39]