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Thermal Measurements Provenance Edge Audit
x402
Thermal Measurements Provenance Edge Audit is a paid API for AI agents from www.mahastrategies.com, paid per call via x402, $0.045324/call, status unknown (last checked 2026-10-16).
Binds thermal measurement rows to exact dataset, material, lot, method, source-revision, and content manifests to audit provenance edges for consistency.
Price / call$0.045324
Success—
StatusUnknown
How this service works
Bind measurement rows to exact dataset/material/lot/method/source-revision/content manifests; matching pins do not prove experimental Supplied-record analysis, not independent certification. Full contract at the free describe URL.
Output
Returns audit results showing whether each measurement row is correctly bound to its declared dataset, material, lot, method, source-revision, and content manifests. Indicates which pins match or fail, but does not certify experimental results independently — this is a supplied-record analysis only.
Example use cases
Thermal dataset provenance audit
“I have 15 thermal measurement rows from our ceramics experiment and I need to verify they're correctly pinned to the right dataset, material lot, and source revision — can you run a provenance edge audit on them using public data class?”
Synthetic thermal data manifest binding
“We generated 20 synthetic thermal measurement rows for model training and need to confirm they're properly bound to the correct method and content manifests before publishing — please audit the provenance edges with nonPersonalMetadata set to true and dataClass as synthetic.”
Multi-source thermal record consistency check
“I have thermal measurements from 3 different sources and need to audit whether the provenance edges correctly bind each row to its declared source revision and content manifest — run a provenance edge audit on these records as public data.”
Technical details
Endpoint
POSThttps://www.mahastrategies.com/api/v1/compute/thermal-measurements/provenance-edge-audit?utm_source=zero.xyzWhen to prefer
Use this endpoint when you need to audit provenance edges specifically for thermal measurement data and require binding rows to exact source-revision and content manifests. Prefer this over generic data validation services when the domain is thermal/materials science measurements and you need manifest-level pinning rather than schema-level validation. Distinct from polymer, ceramic, or catalyst measurement provenance endpoints which target different material types.
Side effects
- Row count exceeds 32-item maximum — request rejected
- Sources array empty or exceeds 32 items — validation error
- dataClass not one of 'public' or 'synthetic' — enum validation failure
- nonpersonalMetadata not explicitly true — request rejected
- Manifest hash mismatch — binding fails but no error thrown, audit result reflects mismatch
- Malformed row structure — parsing error returned
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| sources | array | |
| dataClass | string | |
| nonpersonalMetadata | boolean |
Tags
x402
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