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Label Review Analytics: Trailing Mean Series + Secondary-Measure Weighted Mean
x402
Label Review Analytics: Trailing Mean Series + 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 2026-11-03).
Computes a trailing mean time series and a secondary-measure weighted mean for label review records (reviewed_records and changed_labels) over up to 200 rows, returning two analytical reports.
Price / call$0.01
Success—
StatusUnknown
How this service works
Label review — Trailing mean series + Secondary-measure weighted mean: Trailing mean series + 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) a trailing mean time series for the selected field (reviewed_records or changed_labels) computed over the specified window, and (2) a secondary-measure weighted mean using the complementary field as weights — both computed locally over the supplied rows without external lookup.
Example use cases
QA team annotation throughput smoothing
“I have daily label review logs with reviewed_records and changed_labels for two dataset groups over the past month. Can you compute a trailing mean series with a window of 5 on reviewed_records, and also get the weighted mean using changed_labels as the secondary measure?”
Label correction rate trend analysis
“Run a trailing mean analysis on my annotation review data — I want to track how changed_labels trends over time with a window of 4, plus a secondary-measure weighted mean, for groups 'vision-dataset' and 'nlp-dataset' across 50 rows of daily records.”
Multi-group dataset review comparison
“I have label review records for three dataset groups across 120 rows, and I want to see both the rolling average of reviewed_records with a window of 7 and the weighted mean weighted by changed_labels — can you compute both reports at once?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-12-151?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need to perform both a trailing/rolling mean time series analysis AND a secondary-measure weighted mean on label review data (reviewed_records, changed_labels) in a single low-cost call. Ideal for ML ops teams monitoring annotation quality over time without needing external data sources or live predictions. The bundled two-report format makes it cost-effective at $0.01 USDC per call for up to 200 rows.
Side effects
- Fewer than 1 or more than 200 rows submitted — request rejected
- Window size smaller than 2 or larger than number of rows — may yield sparse or invalid series
- Missing required fields (row_id, date, reviewed_records, changed_labels) — validation error
- Invalid date format (not YYYY-MM-DD) — schema validation failure
- Null values in numeric fields may affect weighted mean calculation
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| window | integer |
Tags
x402
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