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Label Review Analytics — Base-100 Series + Secondary-Measure Weighted Mean
x402
Label Review Analytics — Base-100 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 2026-10-24).
Computes a base-100 index series and a secondary-measure weighted mean from supplied label review records (reviewed_records, changed_labels) for up to 200 rows.
Price / call$0.01
Success—
StatusUnknown
How this service works
Label review — Base-100 series + Secondary-measure weighted mean: Base-100 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
Two analytical reports computed locally from supplied data: (1) a base-100 index series normalizing the selected field relative to the specified base row, and (2) a secondary-measure weighted mean using the complementary metric as weights — returned for up to 200 input rows per call.
Example use cases
Annotation drift tracking over a sprint
“I have two weeks of daily label review logs across three dataset groups — can you index them to a base-100 series starting from day 1 and also compute the weighted mean of changed_labels weighted by reviewed_records? Here are my 14 rows of data with dates, group names, reviewed_records, and changed_labels.”
Comparing label quality across dataset groups
“Run the base-100 index and weighted mean analytics on my label review export — I want to see how changed_labels are trending relative to the first entry (base index 0) and get a weighted average that accounts for how many records were reviewed each day. I have 50 rows covering October, split across group-alpha and group-beta.”
Quality gate check before model retraining
“Before we kick off retraining, can you analyze our annotation review records from the last 30 days? I need a base-100 index series for reviewed_records and the weighted mean for changed_labels across all groups so I can see if label correction rates are staying within normal range.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-12-166?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have up to 200 rows of label review data and need both a base-100 indexed time series and a weighted mean in a single low-cost call ($0.01 USDC). It is ideal for annotation QA pipelines, MLOps audit workflows, or any offline analytical task where no live data lookup or external prediction is required — just local statistical computation on your supplied records.
Side effects
- More than 200 rows submitted — request exceeds maxItems limit
- Missing required fields (row_id, date, reviewed_records, or changed_labels) cause validation error
- Date values not matching YYYY-MM-DD pattern are rejected
- base_index out of range (0–199) causes error
- Null values for both numeric fields may produce undefined weighted mean
- Invalid field enum value (must be 'reviewed_records' or 'changed_labels')
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| base_index | integer |
Tags
x402
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