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Moderation Queues — Secondary-Measure Weighted Mean + Explicit Missing-Value Fill
x402
Moderation Queues — Secondary-Measure Weighted Mean + Explicit Missing-Value Fill is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-30).
Computes a secondary-measure weighted mean and fills missing values in moderation queue records (reported_items, reviewed_items) for up to 200 rows, returning two analytical reports.
Price / call$0.01
Success—
StatusUnknown
How this service works
Moderation queues — Secondary-measure weighted mean + Explicit missing-value fill: Secondary-measure weighted mean + Explicit missing-value fill for supplied moderation queues records (reported_items, reviewed_items). 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 covering: (1) the secondary-measure weighted mean for the selected field (reported_items or reviewed_items) across the supplied rows, and (2) the dataset with missing values explicitly filled using the chosen method (zero, mean, or median). Results are computed locally without external lookups.
Example use cases
Weekly moderation backlog analysis
“I have a CSV export of our moderation queue for last week — about 120 rows with channel_group, date, reported_items, and reviewed_items, but some reviewed_items entries are blank. Can you compute the weighted mean for reviewed_items and fill those blanks using the median method?”
Cross-channel reporting item comparison
“I need to compare reported_items across our content moderation channels. Here are 80 rows grouped by channel_group and date — a few reported_items values are missing. Please compute the weighted mean for reported_items and fill the gaps with zeros.”
Trust and safety data quality pass
“Before I hand off this moderation queue dataset to our analytics team, can you run a weighted mean calculation on reviewed_items and do an explicit missing-value fill using mean imputation? I've got about 150 rows with row_id, channel_group, date, reported_items, and reviewed_items.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-news-06-187?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need both a weighted mean computation and missing-value imputation on moderation queue data (reported_items/reviewed_items) in a single low-cost call. Ideal for offline/batch statistical pre-processing of up to 200 rows where no live data lookup or prediction is needed. The flat $0.01 USDC fee covering two reports makes it cost-efficient for routine moderation analytics pipelines.
Side effects
- Exceeds 200-row limit — request rejected, split data into batches
- Missing required fields (row_id, channel_group, date) — validation error
- Invalid date format (not YYYY-MM-DD) — schema validation failure
- All values for the selected field are null — weighted mean cannot be computed
- Invalid enum for field or method parameters — schema rejection
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| method | string |
Tags
x402
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