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Feedback Theme Low-Confidence Review Queue
x402
Feedback Theme 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 2026-10-18).
Identifies low-confidence predictions in a naive-Bayes feedback theme classifier (quality/price/delivery/support) and returns a bounded review queue of up to 200 labelled records for human inspection.
Price / call$0.01
Success—
StatusUnknown
How this service works
Feedback theme - Low-confidence review queue: Low-confidence review queue for Feedback theme. 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 up to 200 records identified as low-confidence predictions by the naive-Bayes feedback theme classifier, indicating which records the model was most uncertain about across the four classes (quality, price, delivery, support), suitable for routing to a human review queue.
Example use cases
Flag uncertain feedback classifications for QA
“I've got a batch of 80 customer feedback texts that my feedback classifier labelled as quality, price, delivery, or support — along with the class probabilities — but I'm worried some predictions are borderline. Can you pull the low-confidence ones into a review queue so my team knows which records to double-check?”
Evaluate naive-Bayes feedback model weak spots
“My naive-Bayes feedback theme model just ran on 120 records and I want to see where it's least confident — send the predicted labels, actual labels, and probabilities through the low-confidence review queue so I can understand where the model is struggling between quality, price, delivery, and support.”
Prioritise human review of ambiguous support tickets
“We labelled 150 support tickets with actual and predicted feedback themes and have the four-class probabilities from our classifier — can you generate a low-confidence review queue so we know which tickets have the most ambiguous theme predictions and should be reviewed first?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-sector-ml-feedback-theme-review-queue?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have a local naive-Bayes feedback theme classifier producing four-class (quality, price, delivery, support) predictions with probability scores, and you need to programmatically extract the most uncertain or borderline predictions for human review. It is ideal for small datasets (up to 200 records) where you want a lightweight, hosted review-queue step without spinning up a full MLOps pipeline or foundation model. Prefer it over manual filtering when you want a consistent, bounded deliverable at low cost ($0.01 USDC per call).
Side effects
- More than 200 records supplied — input array exceeds maximum limit
- Missing required fields (id, text, actual, predicted, probabilities) on any record
- Probabilities array does not have exactly 4 elements summing to approximately 1
- Invalid enum value for actual or predicted (must be quality, price, delivery, or support)
- Payment not completed — x402 payment required before response is returned
- Empty records array supplied — no records to evaluate
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| records | array | |
| minimum_confidence | number |
Tags
x402
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