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Meeting Topic Supplied-Group Evaluation
x402
Meeting Topic Supplied-Group Evaluation 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).
Evaluates a supplied set of labelled meeting-topic text records (planning/progress/decision/review) broken down by group, computing classification metrics and naive-Bayes baselines per segment.
Price / call$0.01
Success—
StatusUnknown
How this service works
Meeting topic - Supplied-group evaluation: Supplied-group evaluation 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 supplied-group evaluation deliverable.
Output
Returns a bounded evaluation deliverable containing per-group classification metrics (e.g. accuracy, precision, recall) for each meeting topic class (planning, progress, decision, review), along with naive-Bayes baseline comparisons, computed locally from up to 200 supplied labelled text records.
Example use cases
Team-split classifier audit
“I ran a meeting topic classifier over notes from our engineering and product teams. I have 150 records with actual labels and predicted labels — planning, progress, decision, or review — and I want to see accuracy and other metrics broken down by team. Can you evaluate the results by group for me?”
Naive-Bayes baseline comparison
“I'm building a meeting topic model and want to compare it against a naive-Bayes baseline. I have 120 labelled records across two groups with actual and predicted categories (planning, progress, decision, review). Can you run the supplied-group evaluation so I can see how my model stacks up per segment?”
Classifier fairness check across departments
“Before deploying our meeting summariser, I need to check whether it performs equally well across different departments. I have 180 labelled records tagged with department groups and actual vs predicted meeting topic labels. Please run the group evaluation and flag any big accuracy gaps between groups.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-sector-ml-meeting-topic-group-evaluation?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have a small dataset (up to 200 records) of already-labelled meeting text with both actual and predicted topic categories and you need group-stratified classification metrics plus a naive-Bayes baseline — without requiring a hosted model or foundation-model training. Prefer it over general ML evaluation tools when the classification task is specifically the four meeting topic categories (planning, progress, decision, review) and group-level breakdowns are required.
Side effects
- More than 200 records supplied — exceeds the bounded limit, request rejected
- Missing required fields (id, text, actual, predicted, group) on any record — validation error
- Invalid enum value for actual or predicted (must be planning, progress, decision, review) — schema error
- Empty records array — no data to evaluate, returns error
- Text field exceeds 1000 characters per record — truncation or rejection
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| records | array |
Tags
x402
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