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MolTrace · Knowledge Library
Ingest, extract, review, and reuse scientific, analytical, reaction, regulatory, and internal knowledge.
Human review required
Extracted knowledge requires human review. Citations, provenance, and dataset splits must be preserved before records are used for models or regulatory decisions.
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Approved dataset snapshots ready for ML training — versions in snapshot: 0
Scientific literature and structured knowledge sources registered for extraction and review.
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Recent knowledge extraction pipeline runs — source, status, extracted entity count, and run timestamp.
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Extracted knowledge claims pending expert review — status, source, and entity type for each queued review task.
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Reviewed knowledge claims nominated as training data for ML models — type, source, and curation status.
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Knowledge claims nominated as held-out benchmark evaluation data — type, source, and curation status.
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Active model improvement signals — edge cases, failure modes, and feedback items queued for retraining consideration.
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Versioned knowledge dataset snapshots — approval status, entity counts, and provenance for each curated release.
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Knowledge Library lists are operational signals from your tenant API — not legal conclusions or agency positions. See Validation for model validation runs.
Knowledge Extraction · Optional AI Prediction
Optional augmentation only. Existing scientific workflows remain unchanged and human review is required.
Pick a service, attach optional ID anchors (artifact / evidence / compound / session), then provide an input summary JSON. IDs and summaries only — never raw data.
Submit the prediction request to the controlled AI service. Returns a draft prediction that requires human review before use.