# Study Recruitment — Secondary-Measure Weighted Mean + Explicit Missing-Value Fill

> 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.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-education-09-187?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-24
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/study-recruitment-secondary-measure-weighted-mean-explicit-missing-7eeb4e28
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_b6wPgNMbFZBnSIRaunbuG

Status and success rate cover calls made through Zero and Zero's own probes. Third-party monitors may report differently.

## How to call it through Zero

Zero handles the 402 payment challenge and records the run. With the Zero CLI installed (`npm i -g @zeroxyz/cli`):

```sh
zero fetch --capability study-recruitment-secondary-measure-weighted-mean-explicit-missing-7eeb4e28 -d '<json body>'
```

Example prompt: I have 4 study recruitment records across group-a and group-b from October 2026 — can you compute the weighted mean for eligible_candidates and fill any missing values using median imputation? The rows are: row-1 group-a 2026-10-01 eligible=10 enrolled=1, row-2 group-b 2026-10-02 eligible=20 enrolled=2, row-3 group-a 2026-10-03 eligible=15 enrolled=3, row-4 group-b 2026-10-04 eligible=30 enrolled=4.

## When to prefer this

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.

## Known failure modes

- 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

## 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.

## Request schema (JSON Schema)

```json
{
 "type": "object",
 "properties": {
  "rows": {
   "type": "array",
   "items": {
    "type": "object",
    "required": [
     "row_id",
     "course_group",
     "date",
     "eligible_candidates",
     "enrolled_candidates"
    ],
    "properties": {
     "date": {
      "type": "string",
      "default": "",
      "pattern": "^\\d{4}-\\d{2}-\\d{2}$",
      "maxLength": 10
     },
     "row_id": {
      "type": "string",
      "default": "",
      "maxLength": 80,
      "minLength": 1
     },
     "course_group": {
      "type": "string",
      "default": "",
      "maxLength": 80
     },
     "eligible_candidates": {
      "type": [
       "number",
       "null"
      ],
      "maximum": 1000000000000,
      "minimum": -1000000000000
     },
     "enrolled_candidates": {
      "type": [
       "number",
       "null"
      ],
      "maximum": 1000000000000,
      "minimum": -1000000000000
     }
    },
    "additionalProperties": false
   },
   "default": [
    {
     "date": "2026-10-01",
     "row_id": "row-1",
     "course_group": "group-a",
     "eligible_candidates": 10,
     "enrolled_candidates": 1
    },
    {
     "date": "2026-10-02",
     "row_id": "row-2",
     "course_group": "group-b",
     "eligible_candidates": 20,
     "enrolled_candidates": 2
    },
    {
     "date": "2026-10-03",
     "row_id": "row-3",
     "course_group": "group-a",
     "eligible_candidates": 15,
     "enrolled_candidates": 3
    },
    {
     "date": "2026-10-04",
     "row_id": "row-4",
     "course_group": "group-b",
     "eligible_candidates": 30,
     "enrolled_candidates": 4
    }
   ],
   "maxItems": 200,
   "minItems": 1
  },
  "field": {
   "enum": [
    "eligible_candidates",
    "enrolled_candidates"
   ],
   "type": "string",
   "default": "eligible_candidates"
  },
  "method": {
   "enum": [
    "zero",
    "mean",
    "median"
   ],
   "type": "string",
   "default": "median"
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/study-recruitment-secondary-measure-weighted-mean-explicit-missing-7eeb4e28/health.json
- [Zero catalog index](https://www.zero.xyz/llms.txt)
- [Other services from market.datapackvibe.com](https://www.zero.xyz/host/market.datapackvibe.com/llms.txt)