The ground-truth data used in this study is obtained from Pétuya et al.'s work 28 on predicting the guest accessibility of MOFs. This dataset was built from 3D-connected MOF networks made of a single metal and a single linker species in the CSD MOF subset. It was therefore referred to as the 1M1L3D dataset. The available ground-truth data are restricted to a single class of successful synthetic attempts, while negative data from unsuccessful synthetic attempts are comparatively lacking in scale. Under the condition of having extremely unbalanced dataset, OCC is well-suited to discerning the underlying relationships between composition and synthesisability. Taking all of the separate metals and linkers contained in the 1M1L3D dataset, we then generate a larger query dataset of 160,582 potential MOF chemistries by considering every pairwise combination of these metals and linkers that are not contained in the 1M1L3D dataset.