# Content Purpose Classifier – Low-Confidence Review Queue

> Content Purpose Classifier – 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 content-purpose classifier and returns a structured review queue of up to 200 labelled text records for human inspection.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-sector-ml-content-purpose-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/content-purpose-classifier-low-confidence-review-queue-5a9819fc
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_8lGQhTzI676tU2Sg4oeYp

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 content-purpose-classifier-low-confidence-review-queue-5a9819fc -d '<json body>'
```

Example prompt: I have up to 200 labelled text records with actual and predicted content-purpose labels (inform, explain, persuade, instruct) and their class probabilities — can you run them through the low-confidence review queue to flag the ones the model was most uncertain about?

## When to prefer this

Choose this endpoint when you have a local content-purpose text classification dataset with predicted labels and class probabilities and want to automatically surface the low-confidence cases for human review. It is ideal for human-in-the-loop QA workflows, pre-deployment audits, or iterative relabelling pipelines where you need a bounded, cost-effective review queue without hosting a model or calling a foundation model API.

## Known failure modes

- More than 200 records submitted — input exceeds the maximum batch size
- Probabilities array does not contain exactly 4 values per record — schema validation error
- Probabilities values outside [0,1] range — rejected at input validation
- Missing required fields (id, text, actual, predicted, probabilities) — schema validation failure
- Label values outside allowed enum (inform, explain, persuade, instruct) — rejection
- Empty records array — no output produced

## How this service works

Content purpose - Low-confidence review queue: Low-confidence review queue for Content purpose. 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 the subset of submitted records where the classifier's predicted content-purpose label (inform, explain, persuade, instruct) fell below confidence thresholds, enabling targeted human review and relabelling. Includes flagged record IDs, texts, actual vs predicted labels, and associated probabilities.

## 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": [
       "inform",
       "explain",
       "persuade",
       "instruct"
      ],
      "type": "string"
     },
     "predicted": {
      "enum": [
       "inform",
       "explain",
       "persuade",
       "instruct"
      ],
      "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": "inform sample document number 0 for this supplied dataset.",
     "actual": "inform",
     "predicted": "inform",
     "probabilities": [
      0.8,
      0.06666666666666667,
      0.06666666666666667,
      0.06666666666666667
     ]
    },
    {
     "id": "example-0-1",
     "text": "inform sample document number 1 for this supplied dataset.",
     "actual": "inform",
     "predicted": "inform",
     "probabilities": [
      0.8,
      0.06666666666666667,
      0.06666666666666667,
      0.06666666666666667
     ]
    },
    {
     "id": "example-0-2",
     "text": "inform sample document number 2 for this supplied dataset.",
     "actual": "inform",
     "predicted": "inform",
     "probabilities": [
      0.8,
      0.06666666666666667,
      0.06666666666666667,
      0.06666666666666667
     ]
    },
    {
     "id": "example-1-0",
     "text": "explain sample document number 0 for this supplied dataset.",
     "actual": "explain",
     "predicted": "explain",
     "probabilities": [
      0.06666666666666667,
      0.8,
      0.06666666666666667,
      0.06666666666666667
     ]
    },
    {
     "id": "example-1-1",
     "text": "explain sample document number 1 for this supplied dataset.",
     "actual": "explain",
     "predicted": "explain",
     "probabilities": [
      0.06666666666666667,
      0.8,
      0.06666666666666667,
      0.06666666666666667
     ]
    },
    {
     "id": "example-1-2"
… (truncated)
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/content-purpose-classifier-low-confidence-review-queue-5a9819fc/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)