# Review Aspect Low-Confidence Review Queue

> Review Aspect 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 predictions in a naive-Bayes aspect classifier (performance/appearance/value/other) and returns a prioritized queue of records needing human review.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-sector-ml-review-aspect-review-queue?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-12
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/review-aspect-low-confidence-review-queue-249e7e13
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_xJTLBjn3qR0zFl9Q9YtMO

Status and success rate cover calls made through Zero and Zero's own probes. Third-party monitors may report differently.

## How to call it through Zero

Zero handles the 402 payment challenge and records the run. With the Zero CLI installed (`npm i -g @zeroxyz/cli`):

```sh
zero fetch --capability review-aspect-low-confidence-review-queue-249e7e13 -d '<json body>'
```

Example prompt: I ran my aspect classifier over 150 product reviews and got back predicted labels (performance, appearance, value, other) with probabilities — can you give me a low-confidence review queue so I know which records a human annotator should double-check?

## When to prefer this

Choose this endpoint when you have a batch of aspect-classified text records (up to 200) with class probabilities from a local naive-Bayes or small model and need to identify which predictions are uncertain enough to warrant human review. Ideal for human-in-the-loop annotation workflows, active learning pipelines, or pre-deployment validation of aspect classifiers targeting performance, appearance, value, and other categories. Not suitable if you need full model training, hosted inference, or foundation-model fine-tuning.

## Known failure modes

- Records array exceeds 200 items — request rejected or truncated
- Probabilities array does not contain exactly 4 values — validation error
- Predicted or actual label not in allowed enum (performance, appearance, value, other) — schema error
- Empty records array — returns empty queue or error
- Malformed probability values outside [0,1] range — validation failure
- Payment of 0.01 USDC not completed — 402 Payment Required response

## How this service works

Review aspect - Low-confidence review queue: Low-confidence review queue for Review aspect. 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 filtered and prioritized list of submitted records where the classifier's predicted probabilities fall below confidence thresholds, indicating which records most need human review. Includes record IDs, text, actual vs. predicted labels, and probability scores for the flagged items.

## Request schema (JSON Schema)

```json
{
 "type": "object",
 "properties": {
  "records": {
   "type": "array",
   "items": {
    "type": "object",
    "required": [
     "id",
     "text",
     "actual",
     "predicted",
     "probabilities"
    ],
    "properties": {
     "id": {
      "type": "string",
      "default": "",
      "maxLength": 80,
      "minLength": 1
     },
     "text": {
      "type": "string",
      "default": "",
      "maxLength": 1000
     },
     "actual": {
      "enum": [
       "performance",
       "appearance",
       "value",
       "other"
      ],
      "type": "string"
     },
     "predicted": {
      "enum": [
       "performance",
       "appearance",
       "value",
       "other"
      ],
      "type": "string"
     },
     "probabilities": {
      "type": "array",
      "items": {
       "type": "number",
       "default": 0,
       "maximum": 1,
       "minimum": 0
      },
      "default": [],
      "maxItems": 4,
      "minItems": 4
     }
    },
    "additionalProperties": false
   },
   "default": [
    {
     "id": "example-0-0",
     "text": "performance sample document number 0 for this supplied dataset.",
     "actual": "performance",
     "predicted": "performance",
     "probabilities": [
      0.8,
      0.06666666666666667,
      0.06666666666666667,
      0.06666666666666667
     ]
    },
    {
     "id": "example-0-1",
     "text": "performance sample document number 1 for this supplied dataset.",
     "actual": "performance",
     "predicted": "performance",
     "probabilities": [
      0.8,
      0.06666666666666667,
      0.06666666666666667,
      0.06666666666666667
     ]
    },
    {
     "id": "example-0-2",
     "text": "performance sample document number 2 for this supplied dataset.",
     "actual": "performance",
     "predicted": "performance",
     "probabilities": [
      0.8,
      0.06666666666666667,
      0.06666666666666667,
      0.06666666666666667
     ]
    },
    {
     "id": "example-1-0",
     "text": "appearance sample document number 0 for this supplied dataset.",
     "actual": "appearance",
     "predicted": "appearance",
     "probabilities": [
      0.06666666666666667,
      0.8,
      0.06666666666666667,
      0.06666666666666667
     ]
    },
    {
     "id": "example-1-1",
     "text": "appearance sample document number 1 for this supplied dataset.",
     "actual": "appearance",
     "predicted": "appearance",
     "probabilities": [
      0.06666666666666667,
      0.8,
      0.06666666666666667,
   
… (truncated)
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/review-aspect-low-confidence-review-queue-249e7e13/health.json
- [Zero catalog index](https://www.zero.xyz/llms.txt)
- [Other services from market.datapackvibe.com](https://www.zero.xyz/host/market.datapackvibe.com/llms.txt)