# Document Type Confidence Calibration Bins

> Document Type Confidence Calibration Bins is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-28).

Computes confidence calibration bins for a document-type classifier (invoice, report, correspondence, other) from up to 200 labelled prediction records with associated probabilities.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-sector-ml-document-type-calibration?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-28
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/document-type-confidence-calibration-bins-1d853c1a
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_2bmbceaXXylylgqjsbNAq

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 document-type-confidence-calibration-bins-1d853c1a -d '<json body>'
```

Example prompt: I have up to 200 labelled document records where each record has an id, the document text, the actual type (invoice, report, correspondence, or other), the predicted type, and a 4-element probability array — can you compute the confidence calibration bins to see how well my classifier's predicted probabilities match real accuracy?

## When to prefer this

Choose this endpoint when you need to evaluate the probability calibration of a document-type classifier operating over invoice, report, correspondence, and other categories, and you have up to 200 labelled prediction records with class probabilities. It is a lightweight, pay-per-call tool suited for spot evaluation and audit rather than large-scale training pipelines or deep learning retraining workflows.

## Known failure modes

- Fewer than the minimum required records provided — returns error or degenerate bins
- Probability arrays that do not sum to 1 or contain out-of-range values — validation error
- Mismatch between number of classes and probability vector length (must be exactly 4) — schema error
- Records exceeding 200 — truncation or rejection
- Text fields exceeding 1000 characters — truncation or schema rejection
- Empty records array — error response

## How this service works

Document type - Confidence calibration bins: Confidence calibration bins for Document type. 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 confidence calibration bins deliverable.

## Output

A set of confidence calibration bins summarizing how well the classifier's predicted probability scores align with observed accuracy across binned probability ranges, including per-bin statistics useful for reliability diagrams and calibration error analysis.

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

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/document-type-confidence-calibration-bins-1d853c1a/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)