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Label Review Analytics: Exact Row Deduplication + Secondary-Measure Weighted Mean
x402
Label Review Analytics: Exact Row Deduplication + Secondary-Measure Weighted Mean is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-15).
Deduplicates exact rows and computes a secondary-measure weighted mean across label review records (reviewed_records and changed_labels) for up to 200 rows, returning two analytical reports.
Price / call$0.01
Success—
StatusUnknown
How this service works
Label review — Exact row deduplication + Secondary-measure weighted mean: Exact row deduplication + Secondary-measure weighted mean 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 analytical reports: (1) an exact row deduplication report identifying and removing fully duplicate rows from the supplied label review records, and (2) a secondary-measure weighted mean report computing the weighted average of the specified field (reviewed_records or changed_labels) using the other measure as weights, all computed locally without external lookups.
Example use cases
Annotation quality audit deduplication
“I exported our weekly label review log and I think there are duplicate entries — can you remove exact duplicate rows and give me a weighted mean of reviewed_records, grouped across dataset_group values? I have about 150 rows with row_id, date, dataset_group, reviewed_records, and changed_labels.”
Label change rate weighted summary
“I want to understand our label correction rate: run exact deduplication and then compute the weighted mean of changed_labels across my review records. I have 80 rows covering dataset groups 'group-a' and 'group-b' with dates in October 2026.”
ML pipeline label review QA report
“Before we retrain the model, I need a QA report on our label review data — deduplicate any exact duplicate rows and compute the weighted mean for reviewed_records. There are 200 rows with row_id, date, dataset_group, reviewed_records, and changed_labels columns.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-12-051?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have label review tabular data (up to 200 rows) and need both exact row deduplication and a weighted mean computation in a single low-cost call ($0.01 USDC). It is ideal for ML annotation pipelines that need lightweight, local analytics without any external data access, live prediction, or professional assessment. Prefer it over general-purpose analytics tools when you need a bundled two-report output specifically structured around reviewed_records and changed_labels metrics.
Side effects
- Input array exceeds 200 rows — request rejected
- Missing required fields (row_id, date, reviewed_records, changed_labels) on any row — validation error
- Invalid date format (must match YYYY-MM-DD pattern) — schema validation failure
- Numeric values outside allowed range (-1,000,000,000,000 to 1,000,000,000,000) — rejected
- Empty rows array (minItems: 1 not met) — rejected
- Invalid field enum value (must be reviewed_records or changed_labels) — rejected
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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