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Study Recruitment — Secondary-Measure Weighted Mean + Explicit Missing-Value Fill
x402
Study Recruitment — 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 2026-10-24).
Computes a secondary-measure weighted mean and fills missing values explicitly for up to 200 study recruitment records covering eligible and enrolled candidates.
Price / call$0.01
Success—
StatusUnknown
How this service works
Study recruitment — Secondary-measure weighted mean + Explicit missing-value fill: Secondary-measure weighted mean + Explicit missing-value fill for supplied study recruitment records (eligible_candidates, enrolled_candidates). 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 per call: (1) a secondary-measure weighted mean computed across the supplied recruitment rows for the chosen field (eligible_candidates or enrolled_candidates), and (2) an explicitly missing-value-filled dataset using the selected method (zero, mean, or median). Covers up to 200 input rows with no external lookups.
Example use cases
Clinical trial enrollment weighted summary
“I have recruitment data from our Phase 2 trial — 150 rows across 5 study sites with dates, eligible candidates, and enrolled candidates per day. Can you compute the weighted mean for enrolled_candidates and fill any nulls using mean imputation, then give me the two analytical reports?”
Missing value imputation for education cohort
“Our education study has some missing eligible_candidates values across 80 recruitment records. Can you fill those gaps using zero fill and also compute the weighted mean for eligible_candidates across all course groups?”
Recruitment analytics for grant reporting
“I need to produce two reports on our study recruitment data — 60 rows covering group-a and group-b from last quarter. Please compute the weighted mean for enrolled_candidates and use median to fill any missing values before reporting.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-education-09-187?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have tabular study recruitment data (eligible and enrolled candidates) and need both a weighted mean computation and missing-value imputation in a single call. It is purpose-built for research or education recruitment analytics on supplied data up to 200 rows, with no external lookups or live data dependencies. Prefer it over generic statistics APIs when you need exactly two co-produced reports (weighted mean + filled dataset) on candidate enrollment fields.
Side effects
- Input array exceeds 200 rows — request rejected
- Missing required fields (row_id, date, eligible_candidates, enrolled_candidates) — validation error
- Date field does not match YYYY-MM-DD pattern — schema validation failure
- Numeric field values outside allowed range — rejection
- Invalid enum value for field or method parameters — error response
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| method | string |
Tags
x402
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