After the 𝐾-fold CV is finished, the best model is used to predict the label values of the testing subset to determine the final model's performances towards both the training and testing data. The model can then be stored on hard drive alongside its parameters to be loaded by ArchOnML for predictions later on. Finally, when the model has been successfully stored, the descriptors for the prediction set (i.e. the remaining chemical space) need to be calculated. For this purpose, one can either make use of notebook "01" again, or start individual instances of ArchOnML in parallel to speed up the generation process of all remaining inputs. Note, though, that the prediction set will only require the initial structure pre-optimization in SQC quality, as well as the respective SP calculation.