# Product Category Multiclass Brier Score

> Product Category Multiclass Brier Score 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).

Computes the multiclass Brier score for product category text classification predictions across apparel, home, electronics, and other classes.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-sector-ml-product-category-brier?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-15
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/product-category-multiclass-brier-score-912b0200
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_ZVBYxJmq0HwHPFqnH5s37

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 product-category-multiclass-brier-score-912b0200 -d '<json body>'
```

Example prompt: Can you compute the multiclass Brier score for my product category classifier? I have 50 labeled records with text, the actual categories (apparel, home, electronics, or other), predicted categories, and four-element probability vectors for each — I want to know how well-calibrated my probability predictions are.

## When to prefer this

Choose this endpoint when you need a fast, inexpensive ($0.01 USDC) evaluation of probability calibration for a text classifier operating over the specific product categories of apparel, home, electronics, and other. It is ideal for lightweight local evaluation without access to a hosted ML platform, or when you want a standardized Brier score deliverable for up to 200 records without setting up your own evaluation pipeline.

## Known failure modes

- Probability arrays not summing to 1 or containing values outside [0,1] may cause validation errors
- Records missing required fields (id, text, actual, predicted, probabilities) will be rejected
- Submitting more than 200 records may exceed the allowed limit and result in an error
- Invalid actual or predicted category values outside the four allowed enums will fail schema validation
- Empty records array returns no meaningful score

## How this service works

Product category - Multiclass Brier score: Multiclass Brier score for Product category. 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 multiclass brier score deliverable.

## Output

Returns a bounded multiclass Brier score value for the submitted product category predictions, quantifying how well the predicted class probabilities match the true one-hot encoded labels. Lower scores indicate better calibration. The result covers up to 200 labeled records across the four product categories: apparel, home, electronics, and other.

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

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/product-category-multiclass-brier-score-912b0200/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)