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Scientific Dataset Records - Duplicate Identity Detector
x402
Scientific Dataset Records - Duplicate Identity Detector is a paid API for AI agents from www.mahastrategies.com, paid per call via x402, $0.010338/call, status unknown (last checked 2026-10-16).
Groups scientific dataset records by declared organization, record, and revision identities to detect and surface duplicate entries across sources, jurisdictions, and record kinds.
Price / call$0.010338
Success—
StatusUnknown
How this service works
Group declared organization/record/revision identities and compare every source, jurisdiction, record-kind and content Supplied-record analysis, not independent certification. Full contract at the free describe URL.
Output
Returns grouped sets of dataset rows that share declared organization, record, and revision identities, with comparisons broken down by source, jurisdiction, record kind, and content pins. The analysis highlights duplicate clusters but does not independently certify records.
Example use cases
Deduplicating a public research dataset
“I have a set of 20 public scientific dataset records from multiple sources — can you group them by declared organization and revision identity and tell me which ones are duplicates?”
Cross-jurisdiction duplicate audit
“Run a duplicate identity check on these 15 synthetic scientific dataset rows, grouping by source and jurisdiction so I can see which records conflict or repeat across regions.”
Pre-ingestion dataset quality check
“Before I ingest these 30 scientific dataset records, scan them for duplicate record identities across all record kinds and content pins — use the public data class setting and flag any grouped duplicates.”
Technical details
Endpoint
POSThttps://www.mahastrategies.com/api/v1/intel/scientific-dataset-records/duplicate-record-identities?utm_source=zero.xyzWhen to prefer
Use this endpoint when you need to detect duplicate scientific dataset records by comparing declared identity fields (organization, record, revision) across multiple sources and jurisdictions, especially as a pre-ingestion or data-quality audit step. Prefer this over generic deduplication tools when working specifically with scientific dataset metadata in public or synthetic data classes with nonpersonal metadata constraints.
Side effects
- Rows array empty or exceeds 32-item limit — validation error
- dataClass not set to 'public' or 'synthetic' — enum validation failure
- nonpersonalMetadata not set to true (const constraint) — request rejected
- Malformed row objects with missing declared identity fields — incomplete grouping results
- Payment not completed via x402 protocol — 402 Payment Required response
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| dataClass | string | |
| nonpersonalMetadata | boolean |
Tags
x402
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