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Citation Inventories — Record Quality Audit + String Normalisation + Two-Measure Correlation
x402
Citation Inventories — Record Quality Audit + String Normalisation + Two-Measure Correlation is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-26).
Runs three analytical reports (record quality audit, string normalisation, and two-measure correlation) on up to 200 citation inventory rows containing reference_count and verified_references fields.
Price / call$0.01
Success—
StatusUnknown
How this service works
Citation inventories — Record quality audit + String normalisation + Two-measure correlation: Record quality audit + String normalisation + Two-measure correlation for supplied citation inventories records (reference_count, verified_references). Up to 200 rows; 3 independent reports using shared local analytical engines. No live lookup, prediction, professional assessment or external action. 0.01 USDC includes 3 supplied-data reports for up to 200 rows.
Output
Returns three independent analytical reports: (1) a record quality audit flagging completeness, consistency, and validity issues in the citation rows; (2) a string normalisation report cleaning and standardising text fields like document_group; and (3) a two-measure correlation report quantifying the statistical relationship between reference_count and verified_references across the supplied rows. No external lookups or live data fetching are performed.
Example use cases
Academic citation dataset quality check
“I have a spreadsheet of citation records with reference_count and verified_references for several document groups across different dates. Can you audit them for data quality issues, normalise the string fields, and tell me how correlated reference_count and verified_references are?”
Publisher reference verification audit
“We've collected citation inventory data for about 150 journal articles across two groups, and I need three reports: a quality audit on the records, a string normalisation pass, and a correlation analysis between total references and verified ones. Can you run all three?”
Research integrity cross-check
“I want to check whether our verified_references counts are meaningfully correlated with total reference_count across our document groups, and also flag any quality issues or malformed string fields in the citation inventory rows I'm providing.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-writing-06-204?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need three bundled analytical operations — quality audit, string normalisation, and correlation — on citation inventory data in a single cost-effective call. Prefer it over separate single-operation endpoints when you have up to 200 citation rows and want all three reports at once without external data lookups or live verification.
Side effects
- More than 200 rows submitted — request exceeds the maximum batch size
- Missing required fields (row_id, document_group, date, reference_count, or verified_references) causes row rejection
- Malformed date strings not matching YYYY-MM-DD pattern may cause parsing errors
- Null or extreme numeric values outside expected range may affect correlation computation
- Payment of 0.01 USDC not included or declined blocks execution
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array |
Tags
x402
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