To evaluate the automated clustering method on cluster labels based on manual annotations, we performed manual categorization on records related to the adenosine receptors. The concurrence with this manual categorization was evaluated based on multiple metrics (see Table ). The best performance in terms of balance between completeness (extent to which members of the same category are assigned to the same cluster) and homogeneity (extent to which a cluster contains members of a single category) was achieved by using a minimum cluster size of 128. Interestingly, there is a marked difference between the accuracy of clustering for binding and functional assays. The completeness of the functional assays (0.34) is higher than for the binding assays (0.10), which indicates over-segmentation of similar binding assays. For the functional assays a homogeneity of 0.61 is achieved and for binding assays the homogeneity is 0.26. As a side note, the employment of semisupervised UMAP based on assay type or standard type does not improve the clustering accuracy (Table ). The final clustering method (based on non-supervised clustering) leads to a total of 1,027 clusters with a median size of 638 records per cluster and the largest cluster containing 24,105 entries.