Know how much corroboration sits behind a result.
Cross-Source Confidence
Turn source overlap into a usable confidence signal so your team can separate well-supported materials from single-source outliers before making sourcing, simulation, or lab decisions.
Key outcomes
What goes in
Inputs this feature expects
- Any material returned by search or similarity workflows
- Source-level evidence already linked in the warehouse
- Optional filters for provenance or release recency
What comes out
Outputs your team can act on
- A confidence score grounded in source agreement
- Source-by-source corroboration context for review
- A faster way to flag records that need manual scrutiny
Workflow
How teams use Cross-Source Confidence
Resolve the material identity
Lattice Graph normalizes composition and structure identifiers across supported sources.
Compare corroborating evidence
Agreement, disagreement, and source count are rolled into a single decision signal.
Route by trust level
Use the score to auto-sort candidates for automation, review, or rejection.
Best fit
Where this feature fits best
- Teams reconciling conflicting public data
- Confidence-aware ranking and reporting
- Any workflow where provenance quality matters as much as performance
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