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Issue Kind Low-Confidence Review Queue
x402
Issue Kind Low-Confidence Review Queue is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-24).
Returns a low-confidence review queue for a naive-Bayes issue-kind classifier, flagging up to 200 labelled text records where the model's predictions are uncertain.
Price / call$0.01
Success—
StatusUnknown
How this service works
Issue kind - Low-confidence review queue: Low-confidence review queue for Issue kind. 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 low-confidence review queue deliverable.
Output
A bounded deliverable containing the low-confidence review queue: a filtered and ranked list of the submitted records where the naive-Bayes classifier's predicted probabilities indicate uncertainty, along with relevant evaluation metadata to guide human review. Up to 200 records are processed per call.
Example use cases
QA pipeline for support ticket triage
“I ran my naive-Bayes issue classifier on 150 support tickets and got back predicted labels and probabilities for each one. Can you send them through the low-confidence review queue so I can pull out the ones where the model was unsure between bug and request?”
Audit mislabelled training data
“I have 80 records with their actual and predicted issue kinds plus probability scores — some of the predictions don't match the actual labels and I want to find which ones had low confidence so I can fix my training set.”
Monitor classifier degradation over time
“Here are 200 freshly classified issues from this week's batch, each with their predicted label and probabilities. Run them through the low-confidence review queue and tell me if the number of uncertain predictions has gone up compared to what I'd expect.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-sector-ml-issue-kind-review-queue?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need to identify uncertain predictions from a naive-Bayes issue-kind classifier on a local dataset (up to 200 records) and want a structured low-confidence review queue without hosting a model or using a foundation model. It is purpose-built for the four-class issue taxonomy (bug, request, question, other) and is best suited for lightweight QA workflows, training data auditing, or classifier monitoring pipelines at minimal cost ($0.01 per call).
Side effects
- Records array exceeds 200 items — request rejected
- Probabilities array does not contain exactly 4 values per record — validation error
- Probabilities values outside [0,1] range — schema validation failure
- Invalid enum value for actual or predicted label (must be bug, request, question, or other) — rejected
- Empty or missing record ID — rejected
- Payment not processed or insufficient USDC balance — 402 response
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| records | array | |
| minimum_confidence | number |
Tags
x402
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