# Meeting Topic Multiclass Log Loss Calculator

> Meeting Topic Multiclass Log Loss Calculator 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 multiclass log loss for a meeting topic classifier across up to 200 labelled text records with four topic categories.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-sector-ml-meeting-topic-log-loss?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-multiclass-log-loss-calculator-c65634e3
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_VJ2fGNr1zDtCcFRIz7CZ9

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-multiclass-log-loss-calculator-c65634e3 -d '<json body>'
```

Example prompt: Compute the multiclass log loss for my meeting topic classifier — I have 50 records where each has the actual label (one of planning, progress, decision, or review) and the predicted probabilities across all four classes. Here's my dataset.

## When to prefer this

Choose this endpoint when you need a quick, cheap ($0.01 USDC) multiclass log loss calculation for a meeting topic classifier with the specific four-class taxonomy (planning, progress, decision, review) and have up to 200 labelled records ready. It is ideal for lightweight model evaluation without needing to set up local ML tooling or pay for expensive hosted evaluation services. Prefer alternatives if you need per-class breakdown metrics, accuracy/F1, or support for more than 200 records at once.

## Known failure modes

- More than 200 records submitted — request exceeds the per-call limit
- Probabilities array does not contain exactly 4 values per record — validation error
- Probability values outside [0,1] range — schema validation failure
- Invalid or unrecognised class label in actual or predicted fields — enum mismatch error
- Empty records array submitted — no data to evaluate
- Payment not processed — x402 payment required error

## How this service works

Meeting topic - Multiclass log loss: Multiclass log loss 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 multiclass log loss deliverable.

## Output

Returns a bounded multiclass log loss value computed over the supplied labelled records, reflecting how well the predicted probability distributions match the actual meeting topic labels across the four categories: planning, progress, decision, and review.

## 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": [
       "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": [
      0.06666666666666667,
      0.8,
      0.06666666666666667,
      0.06666666666666667
     ]
    },
    
… (truncated)
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/meeting-topic-multiclass-log-loss-calculator-c65634e3/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)