# Knowledge Topic Classifier – Confidence Calibration Bins

> Knowledge Topic Classifier – 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 2026-10-14).

Computes confidence calibration bins for a naive-Bayes knowledge-topic classifier across 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-knowledge-topic-calibration?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-14
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/knowledge-topic-classifier-confidence-calibration-bins-adbbc7c5
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_GtoXfbHogB_yA-il2aNpZ

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 knowledge-topic-classifier-confidence-calibration-bins-adbbc7c5 -d '<json body>'
```

Example prompt: I have up to 200 labelled knowledge-topic records — each with the document text, the actual category (setup, usage, troubleshooting, or reference), the predicted category, and the four class probabilities — can you run confidence calibration bins on them so I can see how well my model's confidence scores align with its actual accuracy?

## When to prefer this

Choose this endpoint when you need calibration bin metrics specifically for a four-class knowledge-topic classifier (setup, usage, troubleshooting, reference) and have up to 200 labelled records with class probability vectors available. It is ideal for post-training evaluation of naive-Bayes or similar local models where you want to assess probability reliability without sending data to a hosted foundation model. Prefer it over generic calibration libraries when you need a pay-per-call, infrastructure-free evaluation deliverable in an agentic workflow.

## Known failure modes

- Too many records supplied (over 200 items) — request rejected or truncated
- Probability vectors not summing to 1 or containing values outside [0,1] — validation error
- Mismatched enum values in actual/predicted fields (values outside setup/usage/troubleshooting/reference) — schema validation failure
- Fewer than 4 probability values per record (minItems:4 not met) — schema error
- Empty records array — returns empty or degenerate calibration output
- Payment not processed (x402 protocol failure) — 402 response with no result

## How this service works

Knowledge topic - Confidence calibration bins: Confidence calibration bins for Knowledge topic. 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 a set of confidence calibration bins summarizing how well the classifier's predicted probabilities align with observed accuracy across the four knowledge-topic classes (setup, usage, troubleshooting, reference). Each bin groups records by predicted confidence level and reports the mean confidence and actual accuracy within that bin, enabling reliability-diagram analysis and detection 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": [
       "setup",
       "usage",
       "troubleshooting",
       "reference"
      ],
      "type": "string"
     },
     "predicted": {
      "enum": [
       "setup",
       "usage",
       "troubleshooting",
       "reference"
      ],
      "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": "setup sample document number 0 for this supplied dataset.",
     "actual": "setup",
     "predicted": "setup",
     "probabilities": [
      0.8,
      0.06666666666666667,
      0.06666666666666667,
      0.06666666666666667
     ]
    },
    {
     "id": "example-0-1",
     "text": "setup sample document number 1 for this supplied dataset.",
     "actual": "setup",
     "predicted": "setup",
     "probabilities": [
      0.8,
      0.06666666666666667,
      0.06666666666666667,
      0.06666666666666667
     ]
    },
    {
     "id": "example-0-2",
     "text": "setup sample document number 2 for this supplied dataset.",
     "actual": "setup",
     "predicted": "setup",
     "probabilities": [
      0.8,
      0.06666666666666667,
      0.06666666666666667,
      0.06666666666666667
     ]
    },
    {
     "id": "example-1-0",
     "text": "usage sample document number 0 for this supplied dataset.",
     "actual": "usage",
     "predicted": "usage",
     "probabilities": [
      0.06666666666666667,
      0.8,
      0.06666666666666667,
      0.06666666666666667
     ]
    },
    {
     "id": "example-1-1",
     "text": "usage sample document number 1 for this supplied dataset.",
     "actual": "usage",
     "predicted": "usage",
     "probabilities": [
      0.06666666666666667,
      0.8,
      0.06666666666666667,
      0.06666666666666667
     ]
    },
    {
     "id": "example-1-2",
     "tex
… (truncated)
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/knowledge-topic-classifier-confidence-calibration-bins-adbbc7c5/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)