# Meeting Topic Classifier – Top-k Label Coverage

> Meeting Topic Classifier – Top-k Label Coverage 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 top-k label coverage metrics for a naive-Bayes meeting topic classifier across up to 200 labelled text records with 4 categories: planning, progress, decision, review.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-sector-ml-meeting-topic-top-k?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/meeting-topic-classifier-top-k-label-coverage-9358c023
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_dRbxB4daX7OADZyInuBqq

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 meeting-topic-classifier-top-k-label-coverage-9358c023 -d '<json body>'
```

Example prompt: Evaluate the top-2 label coverage for my meeting topic classifier — here are 12 labelled records, each with the actual category (planning, progress, decision, or review), the predicted label, and 4 class probabilities per record.

## When to prefer this

Choose this endpoint when you need a fast, cheap ($0.01 USDC) evaluation metric for a 4-class meeting topic classifier and already have model predictions and probabilities in hand. It is ideal for small local datasets (up to 200 records) where you want to measure top-k coverage without training or calling a hosted model. Prefer it over full retraining pipelines or foundation-model APIs when the goal is purely metric computation on pre-classified records.

## Known failure modes

- More than 200 records submitted — batch size limit exceeded
- Probabilities array length not exactly 4 for each record
- k value outside allowed range of 1–4
- Label values outside the allowed enum (planning, progress, decision, review)
- Malformed record missing required fields (id, text, actual, predicted, probabilities)
- Probabilities not summing to approximately 1.0 per record

## How this service works

Meeting topic - Top-k label coverage: Top-k label coverage for Meeting 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 top-k label coverage deliverable.

## Output

Returns a top-k label coverage score indicating the proportion of records where the true label appears among the top-k highest-probability predicted classes, computed over the supplied batch of up to 200 meeting topic records.

## Request schema (JSON Schema)

```json
{
 "type": "object",
 "properties": {
  "k": {
   "type": "integer",
   "default": 2,
   "maximum": 4,
   "minimum": 1
  },
  "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": [
       "planning",
       "progress",
       "decision",
       "review"
      ],
      "type": "string"
     },
     "predicted": {
      "enum": [
       "planning",
       "progress",
       "decision",
       "review"
      ],
      "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": "planning sample document number 0 for this supplied dataset.",
     "actual": "planning",
     "predicted": "planning",
     "probabilities": [
      0.8,
      0.06666666666666667,
      0.06666666666666667,
      0.06666666666666667
     ]
    },
    {
     "id": "example-0-1",
     "text": "planning sample document number 1 for this supplied dataset.",
     "actual": "planning",
     "predicted": "planning",
     "probabilities": [
      0.8,
      0.06666666666666667,
      0.06666666666666667,
      0.06666666666666667
     ]
    },
    {
     "id": "example-0-2",
     "text": "planning sample document number 2 for this supplied dataset.",
     "actual": "planning",
     "predicted": "planning",
     "probabilities": [
      0.8,
      0.06666666666666667,
      0.06666666666666667,
      0.06666666666666667
     ]
    },
    {
     "id": "example-1-0",
     "text": "progress sample document number 0 for this supplied dataset.",
     "actual": "progress",
     "predicted": "progress",
     "probabilities": [
      0.06666666666666667,
      0.8,
      0.06666666666666667,
      0.06666666666666667
     ]
    },
    {
     "id": "example-1-1",
     "text": "progress sample document number 1 for this supplied dataset.",
     "actual": "progress",
     "predicted": "progress",
     "probabilities": [
      0.066666666666666
… (truncated)
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/meeting-topic-classifier-top-k-label-coverage-9358c023/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)