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Label Review Analytics: Trailing Mean Series + Two-Measure Correlation
x402
Label Review Analytics: Trailing Mean Series + 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 2026-10-15).
Computes a trailing mean time series and a two-measure Pearson-style correlation for label review data (reviewed_records vs changed_labels) over up to 200 rows.
Price / call$0.01
Success—
StatusUnknown
How this service works
Label review — Trailing mean series + Two-measure correlation: Trailing mean series + 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 analytical reports: (1) a trailing mean time series over the selected field (reviewed_records or changed_labels) using the specified window size, and (2) a two-measure correlation between reviewed_records and changed_labels across all provided rows. Results are computed locally from supplied data with no external lookups.
Example use cases
ML annotation quality trend analysis
“I have 60 days of label review logs with reviewed_records and changed_labels per day. Can you compute a rolling average with a window of 7 on reviewed_records and also show me how correlated those two metrics are across the dataset?”
Detecting review efficiency dips
“Run a trailing mean series with window 5 on the changed_labels field for my label audit records — I want to spot where label correction activity spikes relative to reviews, and get the two-measure correlation too.”
Multi-group annotation pipeline QA
“I've got 150 rows of label review data across two dataset groups. Can you calculate the trailing mean with window 4 on reviewed_records and give me the correlation between reviewed_records and changed_labels so I can compare group performance?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-12-150?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have label review or annotation audit tabular data and need both a smoothed time series trend (rolling/trailing mean) and a correlation metric between two numeric measures in a single low-cost call. It is ideal for ML ops, data quality teams, and annotation pipeline analysts who already have the data locally and need lightweight statistical summaries without sending data to a full analytics platform.
Side effects
- Fewer than 2 rows provided — minimum 1 row required but meaningful results need multiple rows
- Window size larger than number of rows — trailing mean will have limited coverage
- Null values in reviewed_records or changed_labels — may reduce correlation sample size
- More than 200 rows submitted — request rejected, exceeds maximum
- Invalid date format (non YYYY-MM-DD) — schema validation failure
- Missing required fields row_id or date — request rejected
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| window | integer |
Tags
x402
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