Once the chemical identities had been vectorised, similarity was calculated by the DBSCAN clustering method. DBSCAN calculates the local density of data points in Euclidean space (synthesis protocols in the case of this study), defined as the number of neighbours closer than a threshold distance from each data point. Clusters are identified as disconnected regions containing a high density of data points, while isolated data points with no connection to a larger cluster as identified as noise.