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Commerce Intent Low-Confidence Review Queue
x402
Commerce Intent 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 2026-10-11).
Identifies and surfaces low-confidence predictions in a commerce intent classifier (browse/purchase/return/other) for up to 200 labelled text records, using local naive-Bayes baselines and evaluation tools.
Price / call$0.01
Success—
StatusUnknown
How this service works
Commerce intent - Low-confidence review queue: Low-confidence review queue for Commerce intent. 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 curated set of records from the submitted batch where predicted commerce intent probabilities fall below confidence thresholds, along with local dataset evaluation metrics and naive-Bayes baseline comparison results for browse, purchase, return, and other classes.
Example use cases
Flag uncertain checkout intent predictions
“I've got 150 customer messages where my classifier predicted 'purchase' but I'm not sure it got them right — here are the actual labels, predicted labels, and 4-class probabilities for each. Can you put together the low-confidence review queue so I know which ones to send to a human reviewer?”
Audit browse vs return misclassifications
“I need to review my commerce intent model's uncertain calls on 80 support tickets — each record has the text, the actual intent (browse, return, purchase, or other), the predicted intent, and the probability scores. Can you surface the low-confidence cases so I can prioritize corrections?”
Baseline evaluation for intent classifier QA
“Before I retrain my commerce intent model, I want to evaluate which of my 200 training examples had the lowest prediction confidence across browse, purchase, return, and other — can you run the low-confidence review queue on my labelled dataset and give me the flagged records?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-sector-ml-commerce-intent-review-queue?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have up to 200 pre-labelled commerce intent records (browse/purchase/return/other) with class probabilities and want to identify low-confidence predictions for human review or model auditing — particularly useful in ML evaluation pipelines where no hosted model is needed and local naive-Bayes baselines suffice. Prefer this over full retraining or foundation-model endpoints when the goal is targeted QA on uncertain predictions rather than generating new labels.
Side effects
- Records array exceeds 200 items — endpoint rejects or truncates input
- Missing required fields (id, text, actual, predicted, probabilities) on any record causes validation error
- Probabilities array not exactly length 4 or values outside [0,1] causes schema rejection
- Empty records array returns empty review queue with no useful output
- Text field exceeds 1000 characters per record causing truncation or rejection
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| records | array | |
| minimum_confidence | number |
Tags
x402
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