Figure 3.

Similarity metrics between the three canonicalized representations of each query molecule

String similarity, as measured with gestalt pattern matching, demonstrates that different canonicalizations result in markedly different strings. Shared token ratio and token length ratio indicate that these strings were tokenized into different inputs to the CLM. Feature similarity demonstrates that the differently canonicalized queries’ token vectors were interpreted differently by the model resulting in increased spread across feature space. Feature similarity was determined by cosine similarity between ChemBERTa vector embeddings. Deviations from 1.0 for each metric represent divergence between canonicalized queries.