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Correction Logs — String Normalisation + Two-Measure Correlation
x402
Correction Logs — 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 2026-11-02).
Normalises string fields and computes a two-measure correlation between correction_count and published_items for up to 200 correction log rows, returning two analytical reports.
Price / call$0.01
Success—
StatusUnknown
How this service works
Correction logs — String normalisation + Two-measure correlation: String normalisation + Two-measure correlation for supplied correction logs records (correction_count, published_items). Up to 200 rows; 2 independent reports using shared local analytical engines. No live lookup, prediction, professional assessment or external action. 0.01 USDC includes 2 supplied-data reports for up to 200 rows.
Output
Two structured analytical reports: (1) a string normalisation report covering the channel_group and other string fields across up to 200 rows, and (2) a two-measure correlation report quantifying the statistical relationship between correction_count and published_items across the supplied rows.
Example use cases
News desk correction rate analysis
“I have a week of correction log data across two channel groups — can you normalise the channel group strings and tell me whether correction_count correlates with published_items? Here are my rows: row-1 on 2026-10-01, group-a, 12 corrections, 100 published; row-2 on 2026-10-02, group-b, 5 corrections, 200 published; row-3 on 2026-10-03, group-a, 20 corrections, 150 published.”
Publisher quality audit across channels
“Run a string normalisation and two-measure correlation report on these correction logs for me — I need to check if higher published_items volumes drive more correction_count across our three channel groups over the past month. I'll supply up to 50 rows.”
Editorial operations data clean-up
“Our correction log exports have messy channel group labels — can you normalise those strings and also compute the correlation between correction_count and published_items for these 10 rows so we can spot which groups have the worst correction rates?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-news-04-033?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have correction log data with both string fields (like channel_group) that need normalisation and two numeric measures (correction_count and published_items) you want correlated, and you want both analyses in a single $0.01 call for up to 200 rows without needing live lookup or prediction.
Side effects
- Missing required fields (row_id, date, channel_group, correction_count, published_items) cause validation errors
- Submitting more than 200 rows exceeds the row limit and will be rejected
- Invalid date format (not YYYY-MM-DD) triggers schema validation failure
- Null values for both numeric measures may prevent correlation computation
- Payment of 0.01 USDC not provided results in 402 Payment Required response
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array |
Tags
x402
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