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Sentiment Low-Confidence Review Queue
x402
Sentiment 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 2026-10-12).
Identifies and queues low-confidence sentiment predictions from a supplied set of labelled text records for human or downstream review, using naive-Bayes baselines.
Price / call$0.01
Success—
StatusUnknown
How this service works
Sentiment - Low-confidence review queue: Low-confidence review queue for Sentiment. 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 listing up to 200 submitted records that fall below confidence thresholds, indicating which sentiment predictions are uncertain and should be reviewed. Includes the flagged record IDs, their actual and predicted labels, and associated class probabilities, enabling downstream human review or relabelling workflows.
Example use cases
QA pass on sentiment classifier output
“I've got a batch of 150 customer review texts with their actual and predicted sentiment labels and probabilities from my naive-Bayes model — can you identify which ones are low-confidence so my team knows what to manually re-check?”
Bootstrapping a new sentiment dataset
“I'm building a training dataset for sentiment analysis and I want to flag which of my 200 auto-labelled records the model was uncertain about — here are the texts, actual labels, predicted labels, and probabilities for each one.”
Audit before model deployment
“Before I ship this sentiment model, I want to pull a low-confidence review queue from my validation set of 180 labelled texts so I can see where predictions are shaky and fix them before going live.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-sector-ml-sentiment-review-queue?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have a local sentiment dataset with existing predicted labels and class probabilities and need to identify which predictions are too uncertain for production use, without access to a hosted model or foundation-model training pipeline. It is best suited for lightweight model evaluation and QA workflows using naive-Bayes baselines on small datasets up to 200 records.
Side effects
- More than 200 records submitted — request exceeds the maximum batch size limit
- Probability arrays not summing to ~1 or not containing exactly 3 values — schema validation failure
- Invalid or missing enum values for 'actual' or 'predicted' fields — rejected with validation error
- Empty records array — no review queue generated
- Payment not completed via x402 protocol — endpoint returns 402 Payment Required
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| records | array | |
| minimum_confidence | number |
Tags
x402
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