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Return Reason Exact Normalised Duplicate Audit
x402
Return Reason 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 return-reason text records to detect exact normalised duplicates within the supplied dataset.
Price / call$0.01
Success—
StatusUnknown
How this service works
Return reason - Exact normalised duplicate audit: Exact normalised duplicate audit for Return reason. 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 duplicate audit report identifying which of the supplied labelled return-reason text records are exact normalised duplicates, including their IDs and relevant match details, bounded to the submitted batch of up to 200 records.
Example use cases
Pre-training data deduplication check
“Before I train my return reason classifier, can you check these 120 labelled records for exact normalised duplicates? Each record has an ID, the return text, and one of the labels: damaged, wrong_item, unwanted, or other.”
Return annotation QA for labelling team
“Our annotation team just labelled 80 customer return descriptions — can you run an exact normalised duplicate audit on them so we can flag any records that are identical after normalisation before we sign off on the batch?”
Ecommerce returns dataset cleaning
“I'm cleaning up our returns dataset — here are 200 records each with an ID, the customer's stated return reason text, and the category label (damaged, wrong_item, unwanted, or other). Can you audit them for exact normalised duplicates so I know which ones to remove?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-sector-ml-return-reason-duplicates?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need a lightweight, deterministic exact-normalised duplicate check on a small batch (up to 200 records) of labelled return-reason text data, particularly before training a classifier or validating annotation quality. It is not a semantic similarity or fuzzy deduplication tool — it only catches exact matches after normalisation. Prefer it over general-purpose deduplication tools when your data specifically uses the return-reason label schema (damaged, wrong_item, unwanted, other) and you want a bounded, low-cost ($0.01 USDC) deliverable with no model training involved.
Side effects
- Fewer than 2 records submitted — minimum record count not met
- More than 200 records submitted — exceeds maximum batch size
- Missing required fields (id, text, or actual) on one or more records
- Invalid enum value for 'actual' field (must be damaged, wrong_item, unwanted, or other)
- Record ID exceeds 80 characters or text exceeds 1000 characters
- Payment not fulfilled via x402 protocol — request rejected
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| records | array |
Tags
x402
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