In this section, we discuss one of the intended uses of the MF-PCBA datasets by evaluating multi-fidelity integration machine learning techniques. We use the same modelling techniques previously proposed by Buterez et al., focusing on the analysis of the additional 37 datasets that complete the collection of 60 datasets, the rest of 23 already being extensively investigated. In order to highlight meaningful differences between the initial collection of 23 multi-fidelity datasets and MF-PCBA, we introduce the following naming conventions: the terms MF-PCBA and MF-PCBA-60 are used interchangeably to refer to the entire collection of 60 multi-fidelity datasets, MF-PCBA-23 refers to the subset analysed in , and MF-PCBA-37 refers to the rest of the 37 datasets that complete the collection of 60 datasets. Thus, MF-PCBA-23 and MF-PCBA-37 are disjoint.