# Language Routing Confidence Calibration Bins

> Language Routing 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 2026-10-15).

Computes confidence calibration bins for a language routing classifier given up to 200 labelled text records with actual labels, predicted labels, and class probabilities.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-sector-ml-language-routing-calibration?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/language-routing-confidence-calibration-bins-03b5883a
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_xllANl1WU__-oru9_JTwL

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 language-routing-confidence-calibration-bins-03b5883a -d '<json body>'
```

Example prompt: I have 150 labelled records from my language routing model — each with the text, the actual language (english, french, spanish, or other), the predicted language, and the four class probabilities — can you compute confidence calibration bins so I can see how well-calibrated the model's confidence scores are?

## When to prefer this

Choose this endpoint when you need to evaluate the calibration quality of a 4-class language routing model (english/french/spanish/other) using your own labelled dataset. It is ideal for offline evaluation workflows, pre-deployment audits, and debugging overconfident or underconfident classifiers without needing a hosted model or foundation-model training infrastructure. At $0.01 per call it is cost-effective for iterative calibration checks on batches up to 200 records.

## Known failure modes

- Fewer than required records provided causing insufficient bin population
- Probabilities array does not sum to 1 or contains values outside [0,1]
- Record missing required fields (id, text, actual, predicted, probabilities)
- More than 200 records submitted exceeding the per-call limit
- Invalid enum value for actual or predicted language label
- Probabilities array does not have exactly 4 elements

## How this service works

Language routing - Confidence calibration bins: Confidence calibration bins for Language routing. 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

Returns confidence calibration bins summarizing how well the classifier's predicted probabilities align with actual accuracy across the confidence spectrum — including bin boundaries, sample counts per bin, mean confidence per bin, and observed accuracy per bin, enabling identification of over- or under-confidence.

## 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": [
       "english",
       "french",
       "spanish",
       "other"
      ],
      "type": "string"
     },
     "predicted": {
      "enum": [
       "english",
       "french",
       "spanish",
       "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": "english sample document number 0 for this supplied dataset.",
     "actual": "english",
     "predicted": "english",
     "probabilities": [
      0.8,
      0.06666666666666667,
      0.06666666666666667,
      0.06666666666666667
     ]
    },
    {
     "id": "example-0-1",
     "text": "english sample document number 1 for this supplied dataset.",
     "actual": "english",
     "predicted": "english",
     "probabilities": [
      0.8,
      0.06666666666666667,
      0.06666666666666667,
      0.06666666666666667
     ]
    },
    {
     "id": "example-0-2",
     "text": "english sample document number 2 for this supplied dataset.",
     "actual": "english",
     "predicted": "english",
     "probabilities": [
      0.8,
      0.06666666666666667,
      0.06666666666666667,
      0.06666666666666667
     ]
    },
    {
     "id": "example-1-0",
     "text": "french sample document number 0 for this supplied dataset.",
     "actual": "french",
     "predicted": "french",
     "probabilities": [
      0.06666666666666667,
      0.8,
      0.06666666666666667,
      0.06666666666666667
     ]
    },
    {
     "id": "example-1-1",
     "text": "french sample document number 1 for this supplied dataset.",
     "actual": "french",
     "predicted": "french",
     "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/language-routing-confidence-calibration-bins-03b5883a/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)