ChemCensor: Reaction Chemical Plausibility Database

ChemCensor is a precedent-based framework for evaluating reaction chemical plausibility. The associated SQLite database supports scoring by separating reaction centers from functional-group context and checking against documented synthetic precedents. It was created by insilicomedicine and last updated on Hugging Face in May 2026.

Use Cases

• Scoring the plausibility of proposed chemical reactions based on documented precedents.
• Training machine learning models to predict reaction feasibility using the separation of reaction centers and functional-group context.
• Validating novel synthetic routes by checking for similar patterns in the database of known reactions.

Strengths

• The database is designed for a specific, documented methodology (ChemCensor framework).
• The dataset was last updated on 2026-05-28, suggesting recent maintenance.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.
• The description metadata is limited; actual data quality requires manual inspection after download.

Provenance

Source

insilicomedicine on Hugging Face

Collection Method

Likely compiled from documented synthetic precedents, though the exact sources are not specified.

Freshness

Last updated 2026-05-28 13:40:23; freshness should be verified.