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Alloy Measurements - Duplicate Record Identity Comparison
x402
Alloy Measurements - Duplicate Record Identity Comparison is a paid API for AI agents from www.mahastrategies.com, paid per call via x402, $0.01032/call, status unknown (last checked 2026-10-16).
Detects and groups duplicate owner/subject/revision declarations in alloy measurement records across scientific frames without independent certification.
Price / call$0.01032
Success—
StatusUnknown
How this service works
Compare duplicate owner/subject/revision declarations against every scientific frame Supplied-record analysis, not independent certification. Full contract at the free describe URL.
Output
Returns grouped sets of duplicate alloy measurement records that share identical owner, subject, and/or revision declarations within scientific frames, enabling callers to identify and resolve redundant entries in their supplied dataset.
Example use cases
Audit alloy dataset before publication
“I have up to 30 alloy measurement rows from our internal synthetic dataset that I need to check for duplicate owner and revision declarations before we publish — can you run them through the duplicate identity check and flag any conflicts?”
QC pipeline for ingested alloy records
“As part of our alloy data ingestion pipeline, I need to compare these 15 newly received public alloy measurement rows for duplicate subject and revision identities so we can reject duplicates before storing them.”
Reconcile alloy records from multiple labs
“We received alloy measurement submissions from three different labs and I suspect there are duplicate entries with the same owner and revision markers — can you analyze these rows as synthetic data and group the duplicates for me?”
Technical details
Endpoint
POSThttps://www.mahastrategies.com/api/v1/compute/alloy-measurements/duplicate-record-identities?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need to detect duplicate identity declarations (owner, subject, revision) within alloy measurement records across scientific frames, especially when working with public or synthetic datasets that carry no personal information. It is a record-analysis tool, not an independent certification service, so prefer it for data quality control and pre-ingestion deduplication rather than authoritative scientific validation.
Side effects
- Empty or missing rows array returns validation error
- rows array exceeding 32 items rejected
- dataClass value outside 'public' or 'synthetic' enum rejected
- nonpersonalMetadata not set to true (const constraint) causes rejection
- Malformed row objects may produce incomplete duplicate groupings
- Network timeout for large row payloads
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| dataClass | string | |
| nonpersonalMetadata | boolean |
Tags
x402
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