To demonstrate how the PAH101 dataset can be reused to train ML models for other purposes than SF, we use SISSO to find predictive models for the GW fundamental band gap, whose values are also provided in the dataset. The dataset can be used in a similar manner to train ML models other than SISSO to predict any of the quantities included in the dataset. In addition, it can be used to supplement larger lower-fidelity datasets to train multi-fidelity models.