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Subscription Request Low-Confidence Review Queue
x402
Subscription Request 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 low-confidence classifier predictions on subscription request text records (upgrade/downgrade/cancel/renew) for human review, using naive-Bayes baselines.
Price / call$0.01
Success—
StatusUnknown
How this service works
Subscription request - Low-confidence review queue: Low-confidence review queue for Subscription request. 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 records where the classifier's predicted probabilities fall below the confidence threshold, identifying which upgrade/downgrade/cancel/renew predictions require human review, along with relevant evaluation metadata from the local naive-Bayes baseline analysis.
Example use cases
Flag uncertain subscription churn predictions
“I've got 150 customer message records labelled for cancel intent — some have probabilities around 0.4 across classes. Can you pull the low-confidence ones into a review queue so my team knows which cancellation predictions to double-check manually?”
QA pass on upgrade classifier outputs
“My naive-Bayes model just ran on 80 subscription upgrade requests. Here are the records with their actual vs predicted labels and probabilities — can you generate the low-confidence review queue so I can see which upgrade predictions are too uncertain to trust?”
Pre-launch model audit for subscription intents
“Before we go live, I want to audit our subscription intent classifier across upgrade, downgrade, cancel, and renew classes. I have 200 labelled records with probabilities — can you give me the low-confidence review queue so we can catch weak spots?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-sector-ml-subscription-request-review-queue?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have a local labelled dataset of subscription request text already classified by a naive-Bayes or similar lightweight model and need to surface the low-confidence predictions for human review before acting on them. It is purpose-built for subscription intent categories (upgrade, downgrade, cancel, renew) and does not require a hosted model or foundation model — ideal for small-scale, cost-sensitive ML quality assurance pipelines.
Side effects
- records array exceeds 200 items — request rejected
- probabilities array does not contain exactly 4 values per record — validation error
- probability values outside [0,1] range — schema rejection
- actual or predicted labels outside allowed enum (upgrade, downgrade, cancel, renew) — validation error
- empty records array returns empty review queue with no actionable output
- malformed record IDs (empty string or over 80 characters) — schema rejection
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| records | array | |
| minimum_confidence | number |
Tags
x402
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