Table 3:

A comparison between ClinVar-BERT and BioBERT on embedding clustering quality of language model embeddings in the d-dimensional space. For each attribute, we report Silhouette scores (higher is better) and Davies-Bouldin indices (lower is better) as mean ± standard deviation computed with 100 independent and randomly sampled runs.

Attribute	ClinVar-BERT		BioBERT
	Silhouette	Davies-Bouldin	Silhouette	Davies-Bouldin
Clinical Significance	0.4376 ± 0.0027	1.4352 ± 0.0091	0.0991 ± 0.0026	4.4854 ± 0.0555
Submission Classification	0.6446 ± 0.0020	0.5278 ± 0.0026	0.1170 ± 0.0029	3.2261 ± 0.0237
Submitter	−0.2696 ± 0.0510	2.8505 ± 0.0883	0.1381 ± 0.0200	1.5892 ± 0.0453