# Training Question Exact Normalised Duplicate Audit

> Training Question Exact Normalised Duplicate Audit is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-12).

Audits up to 200 labelled training question text records to detect exact normalised duplicates within the dataset.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-sector-ml-training-question-duplicates?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-12
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/training-question-exact-normalised-duplicate-audit-6056e0ca
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_IVecMKjMh-tAYwECU5KaK

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 training-question-exact-normalised-duplicate-audit-6056e0ca -d '<json body>'
```

Example prompt: Can you audit my training question dataset for exact normalised duplicates? I have about 150 labelled records, each tagged as concept, procedure, example, or assessment — I want to know which ones are repeated.

## When to prefer this

Use this endpoint when you need a fast, low-cost exact normalised duplicate check on a small-to-medium labelled training question dataset (up to 200 records) before running ML training pipelines. It is purpose-built for training data with categorical labels (concept, procedure, example, assessment) and is ideal for data cleaning workflows where semantic similarity is not required — only exact matches after normalisation.

## Known failure modes

- Fewer than 2 records submitted — minimum input requirement not met
- More than 200 records submitted — exceeds maximum item limit
- Record missing required fields (id, text, or actual) — schema validation error
- Invalid label value outside allowed enum (concept, procedure, example, assessment) — rejected
- Record ID exceeds 80 characters — schema violation
- Text field exceeds 1000 characters — schema violation
- Payment of 0.01 USDC not provided or rejected — 402 response

## How this service works

Training question - Exact normalised duplicate audit: Exact normalised duplicate audit for Training question. Up to 200 supplied labelled text records. Local dataset tools, evaluation and small naive-Bayes baselines; no hosted model or foundation-model training. One of 25 profiles or calculations across 20 shared operations in this sector. 0.01 USDC includes one bounded exact normalised duplicate audit deliverable.

## Output

A bounded exact normalised duplicate audit report identifying which records among the submitted labelled text entries are exact matches after normalisation, including duplicate pairs or groups and counts, enabling data cleaning before model training.

## Request schema (JSON Schema)

```json
{
 "type": "object",
 "properties": {
  "records": {
   "type": "array",
   "items": {
    "type": "object",
    "required": [
     "id",
     "text",
     "actual"
    ],
    "properties": {
     "id": {
      "type": "string",
      "default": "",
      "maxLength": 80,
      "minLength": 1
     },
     "text": {
      "type": "string",
      "default": "",
      "maxLength": 1000
     },
     "actual": {
      "enum": [
       "concept",
       "procedure",
       "example",
       "assessment"
      ],
      "type": "string"
     }
    },
    "additionalProperties": false
   },
   "default": [
    {
     "id": "example-0-0",
     "text": "concept sample document number 0 for this supplied dataset.",
     "actual": "concept"
    },
    {
     "id": "example-0-1",
     "text": "concept sample document number 1 for this supplied dataset.",
     "actual": "concept"
    },
    {
     "id": "example-0-2",
     "text": "concept sample document number 2 for this supplied dataset.",
     "actual": "concept"
    },
    {
     "id": "example-1-0",
     "text": "procedure sample document number 0 for this supplied dataset.",
     "actual": "procedure"
    },
    {
     "id": "example-1-1",
     "text": "procedure sample document number 1 for this supplied dataset.",
     "actual": "procedure"
    },
    {
     "id": "example-1-2",
     "text": "procedure sample document number 2 for this supplied dataset.",
     "actual": "procedure"
    },
    {
     "id": "example-2-0",
     "text": "example sample document number 0 for this supplied dataset.",
     "actual": "example"
    },
    {
     "id": "example-2-1",
     "text": "example sample document number 1 for this supplied dataset.",
     "actual": "example"
    },
    {
     "id": "example-2-2",
     "text": "example sample document number 2 for this supplied dataset.",
     "actual": "example"
    },
    {
     "id": "example-3-0",
     "text": "assessment sample document number 0 for this supplied dataset.",
     "actual": "assessment"
    },
    {
     "id": "example-3-1",
     "text": "assessment sample document number 1 for this supplied dataset.",
     "actual": "assessment"
    },
    {
     "id": "example-3-2",
     "text": "assessment sample document number 2 for this supplied dataset.",
     "actual": "assessment"
    }
   ],
   "maxItems": 200,
   "minItems": 2
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/training-question-exact-normalised-duplicate-audit-6056e0ca/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)