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Label Review — Numeric Interval Filter + Two-Measure Correlation
x402
Label Review — Numeric Interval Filter + 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 2026-10-19).
Filters label review records by a numeric interval on a chosen field and computes a Pearson/Spearman correlation between reviewed_records and changed_labels, returning two analytical reports for up to 200 rows.
Price / call$0.01
Success—
StatusUnknown
How this service works
Label review — Numeric interval filter + Two-measure correlation: Numeric interval filter + Two-measure correlation for supplied label review records (reviewed_records, changed_labels). 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
Returns two independent analytical reports: (1) the subset of rows where the chosen field falls within the specified numeric interval [minimum, maximum], and (2) a two-measure correlation analysis quantifying the statistical relationship between reviewed_records and changed_labels across the supplied (up to 200) rows. No external data is fetched; all computation is performed on the submitted rows.
Example use cases
QA pipeline label change correlation
“I have 120 label review records from our ML annotation pipeline. Filter to rows where changed_labels is between 0 and 50, then tell me how strongly changed_labels correlates with reviewed_records across those rows.”
Dataset group audit interval check
“Can you take my label review CSV — about 90 rows with dataset_group, date, reviewed_records, and changed_labels — filter reviewed_records between 5 and 200, and give me both the filtered data report and the correlation between the two numeric measures?”
Annotation throughput statistical summary
“I want to understand whether high review volume days also have more label changes. Run an interval filter on reviewed_records from 100 to 1000 and compute the two-measure correlation for my 150 label review rows.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-12-131?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have label review data (reviewed_records + changed_labels) and need both a numeric interval filter and a two-measure correlation in a single $0.01 call. It is ideal when you want to scope your data to a meaningful range before assessing whether review volume and label change counts move together. Prefer it over general-purpose analytics when your domain is annotation QA or ML labeling pipelines and your dataset is 200 rows or fewer.
Side effects
- More than 200 rows submitted — request will be rejected or truncated
- Invalid date format (not YYYY-MM-DD) causes row-level validation error
- Null values in both reviewed_records and changed_labels may reduce correlation sample size and produce warnings
- minimum greater than maximum produces an empty interval filter result
- row_id missing or empty causes schema validation failure
- Non-numeric values in numeric fields rejected by schema
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| maximum | number | |
| minimum | number |
Tags
x402
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