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Lead Stage Low-Confidence Review Queue
x402
Lead Stage 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 2026-10-15).
Identifies and surfaces low-confidence predictions from a naive-Bayes lead stage classifier across enquiry, qualified, negotiation, and closed labels for human review.
Price / call$0.01
Success—
StatusUnknown
How this service works
Lead stage - Low-confidence review queue: Low-confidence review queue for Lead stage. 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 flagged records identified as low-confidence by the naive-Bayes lead stage classifier, including record IDs, text, actual vs predicted labels, and probability distributions — formatted as a structured review queue for human inspection.
Example use cases
Audit uncertain lead stage predictions
“I ran our naive-Bayes lead classifier on 120 support emails with actual and predicted labels across enquiry, qualified, negotiation, and closed — can you build me a low-confidence review queue so I know which ones need a human to double-check?”
QA before CRM pipeline update
“Before we push these 80 lead stage classifications into the CRM, can you flag any records where the model probabilities were too close to call? I have the actual labels, predicted labels, and probability arrays ready.”
Identify model weak spots by lead stage
“We're evaluating our lead stage classifier and I want to see where it's least confident — here are 150 text records labeled as enquiry, qualified, negotiation, or closed with their predicted probabilities. Can you pull a low-confidence review queue for us?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-sector-ml-lead-stage-review-queue?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have up to 200 labeled lead stage text records with class probabilities from a naive-Bayes or similar local classifier and need to surface the low-confidence predictions for human review. It is purpose-built for the four-class lead pipeline (enquiry, qualified, negotiation, closed) and requires no hosted or foundation model — ideal for lightweight local evaluation workflows where you want a bounded, low-cost ($0.01 USDC) review queue output without training a new model.
Side effects
- Exceeds 200 record limit — request will be rejected or truncated
- Invalid or mismatched probability array length (must be exactly 4 values summing near 1.0)
- Records missing required fields (id, text, actual, predicted, probabilities) cause validation errors
- Label values outside the enum (enquiry, qualified, negotiation, closed) are rejected
- Empty records array returns an empty or minimal deliverable with no useful flagged items
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| records | array | |
| minimum_confidence | number |
Tags
x402
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