# Protein Measurements Unit-Label Consistency Checker

> Protein Measurements Unit-Label Consistency Checker is a paid API for AI agents from www.mahastrategies.com, paid per call via x402, $0.012314/call, status unknown (last checked 2026-10-20).

Validates unit/quantity compatibility and detects conflicting unit labels within the same dataset/subject/run/method/revision/quantity frame for protein measurement records

## Facts

- Endpoint: POST https://www.mahastrategies.com/api/v1/compute/protein-measurements/unit-label-consistency?utm_source=zero.xyz
- Price: $0.012314/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-20
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/protein-measurements-unit-label-consistency-checker-dfeea03a
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_cvtjB8og-CLw3KI3klh0H

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 protein-measurements-unit-label-consistency-checker-dfeea03a -d '<json body>'
```

Example prompt: Can you check this batch of protein measurement records for conflicting or incompatible unit labels — the data is synthetic and non-personal — and tell me if there are any mismatches within the same dataset, run, and method frame?

## When to prefer this

Use this endpoint when you need to audit protein measurement records specifically for unit label consistency and compatibility conflicts within a shared contextual frame (same dataset, subject, run, method, revision, quantity), without needing numerical unit conversion. Prefer this over generic data validation tools when the domain is protein measurements and the concern is label-level coherence rather than value accuracy.

## Known failure modes

- Array exceeds 32 items — request rejected with validation error
- Missing required nonpersonalMetadata: true field — rejected
- Invalid dataClass value outside 'public' or 'synthetic' enum — rejected
- Empty measurements array — rejected
- Malformed measurement record structure — parsing error returned
- Payment failure via x402 protocol — access denied

## How this service works

Check quantity/unit compatibility and conflicting unit labels only within the same dataset/subject/run/method/revision/quantity frame; never convert numerically for protein measurement Supplied-record analysis, not independent certification. Full contract at the free describe URL.

## Output

A report identifying unit label conflicts and quantity/unit incompatibilities found within matching dataset/subject/run/method/revision/quantity frames in the supplied protein measurement records. Does not perform numerical conversion; only flags consistency issues based on declared labels.

## Request schema (JSON Schema)

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

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/protein-measurements-unit-label-consistency-checker-dfeea03a/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)