# Scientific Dataset Records — Missingness Co-occurrence

> Scientific Dataset Records — Missingness Co-occurrence is a paid API for AI agents from www.mahastrategies.com, paid per call via x402, $0.020338/call, status unknown (last checked 2026-10-15).

Counts joint absence (co-occurrence of missingness) of source, method, and unit declarations across public or synthetic scientific dataset metadata records.

## Facts

- Endpoint: POST https://www.mahastrategies.com/api/v1/intel/scientific-dataset-records/missingness-cooccurrence?utm_source=zero.xyz
- Price: $0.020338/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-15
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/scientific-dataset-records-missingness-co-occurrence-fd8a9e85
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_0hA2LRqDtydEspoqhfzeV

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 scientific-dataset-records-missingness-co-occurrence-fd8a9e85 -d '<json body>'
```

Example prompt: Can you check these 10 public scientific dataset metadata records and count how often source, method, and unit declarations are jointly absent at the same time? Make sure to flag this as non-personal metadata only.

## When to prefer this

Choose this endpoint when you need to quantify how often multiple metadata declaration fields (source, method, unit) are simultaneously absent in public or synthetic scientific dataset records — specifically for offline typed metadata auditing without any imputation, raw specimen data, or scientific validity assessment. Prefer it over single-field missingness checks when the joint co-occurrence pattern across multiple declaration types is what matters.

## Known failure modes

- Submission of more than 32 records returns a validation error
- nonpersonalMetadata must be set to true; calls with false or absent value will be rejected
- dataClass must be exactly 'public' or 'synthetic'; other values cause schema validation failure
- Empty records array (fewer than 1 item) triggers a minimum-items validation error
- Submitting records containing actual specimen data rather than typed metadata may cause rejection
- Result unavailability after 24-hour retention window returns not-found or expired error

## How this service works

Count joint absence of source, method and unit declarations in public/synthetic dataset metadata. No raw specimen data, imputation or scientific validity determination. Offline typed metadata only. Retained-result recovery: 24 hours; minimal receipt metadata: 90 days.

## Output

Returns counts of joint absence (co-occurrence of missingness) for combinations of source, method, and unit declarations across the submitted metadata records, covering up to 32 records per call. Results are retained for 24 hours with minimal receipt metadata kept for 90 days.

## Request schema (JSON Schema)

```json
{
 "type": "object",
 "properties": {
  "records": {
   "type": "array",
   "maxItems": 32,
   "minItems": 1
  },
  "dataClass": {
   "enum": [
    "public",
    "synthetic"
   ],
   "type": "string"
  },
  "nonpersonalMetadata": {
   "type": "boolean",
   "const": true
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/scientific-dataset-records-missingness-co-occurrence-fd8a9e85/health.json
- [Zero catalog index](https://www.zero.xyz/llms.txt)
- [Other services from www.mahastrategies.com](https://www.zero.xyz/host/www.mahastrategies.com/llms.txt)