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Study Notes Missingness Co-occurrence Analyzer
x402
Study Notes Missingness Co-occurrence Analyzer is a paid API for AI agents from www.mahastrategies.com, paid per call via x402, $0.020296/call, status unknown (last checked 2026-10-28).
Counts joint absences of source, locator, and confidence-basis metadata fields across study notes without imputation or quality scoring
Price / call$0.020296
Success—
StatusUnknown
How this service works
Count joint absence of source, locator and confidence-basis metadata in study notes without imputation or a quality score. Offline typed nonpersonal metadata only. Result retention: 24 hours; minimal receipt metadata: 90 days.
Output
Returns counts and co-occurrence patterns of joint absences across source, locator, and confidence-basis metadata fields in the submitted study notes, without any imputation or quality scoring applied. Results are retained for 24 hours; minimal receipt metadata is retained for 90 days.
Example use cases
Research corpus metadata gap audit
“I have 20 study notes from a public dataset and I need to know how often source, locator, and confidence-basis are all missing at the same time — no filling in blanks, just count the joint absences for me. All metadata is nonpersonal and public.”
Systematic bias detection in note metadata
“Can you run a missingness co-occurrence check on these 15 synthetic study notes? I want to see which combinations of source, locator, and confidence-basis fields tend to be absent together, with no imputation applied — nonpersonal metadata only.”
Pre-analysis metadata completeness check
“Before I run my analysis, I'd like to audit these 8 study notes to count how many are jointly missing both source and confidence-basis metadata — treat them as public data, no imputation, and only look at nonpersonal metadata fields.”
Technical details
Endpoint
POSThttps://www.mahastrategies.com/api/v1/context/study-notes/missingness-cooccurrence?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need a raw, unimputed count of joint metadata absences (source, locator, confidence-basis) across study notes and do not need quality scoring or data filling. Ideal for pre-analysis audits, systematic gap detection, and research pipelines that require strict nonpersonal, offline metadata handling with public or synthetic data only.
Side effects
- notes array empty or exceeds 32 items — validation error
- nonpersonalMetadata not set to true — request rejected
- dataClass not one of 'public' or 'synthetic' — schema validation failure
- malformed note objects in array — parsing error
- service unavailable — transient 5xx error
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| notes | array | |
| dataClass | string | |
| nonpersonalMetadata | boolean |
Tags
x402
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