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Task Type Exact Normalised Duplicate Audit
x402
Task Type 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 text records for exact normalised duplicates within a task-type classification dataset (research, writing, analysis, implementation).
Price / call$0.01
Success—
StatusUnknown
How this service works
Task type - Exact normalised duplicate audit: Exact normalised duplicate audit for Task type. 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 duplicate audit report identifying which of the supplied labelled text records are exact normalised duplicates of one another, including the matching record IDs and duplicate groupings, covering up to 200 input records per call.
Example use cases
Pre-training dataset deduplication check
“I have 150 labelled text samples tagged as research, writing, analysis, or implementation that I want to use for training. Can you audit them for exact normalised duplicates so I can remove any redundant entries before I start training?”
Annotation quality review for a content team
“Our annotators labelled 80 task descriptions as either writing or analysis tasks — can you check whether any of those labelled records are exact normalised duplicates of each other so we can flag annotation errors?”
Dataset merge duplicate verification
“I've merged two batches of task-type labelled data into about 120 records total, each tagged research, writing, analysis, or implementation. Please audit the combined set for exact normalised duplicates so I know if any records appear more than once.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-sector-ml-task-type-duplicates?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need a fast, low-cost exact normalised duplicate check on a small-to-medium labelled text dataset (up to 200 records) categorised into task types (research, writing, analysis, implementation). It is ideal for data quality audits before ML training, annotation reviews, or dataset merges where you only need exact match detection rather than semantic similarity. It does not use a hosted model or perform fuzzy/semantic deduplication.
Side effects
- Fewer than 2 records supplied — minimum input not met
- More than 200 records supplied — exceeds maximum item limit
- Records missing required fields (id, text, or actual label)
- Label values outside the allowed enum (research, writing, analysis, implementation)
- Text exceeding 1000 characters per record
- ID exceeding 80 characters
- Payment not provided or insufficient — x402 payment required at $0.01 USDC
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| records | array |
Tags
x402
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