# Meeting minutes evidence classifier

First-pass MiniLM embedding classifier for Trinzo meeting-minutes evidence.

This model is separate from the project-update status classifier. It reuses the
same MiniLM embedding approach, but the labels are minutes-specific:

- `overall_status` means evidence type.
- `action_state` means commitment strength.
- `signals` are supporting evidence cues.

The classifier is intended to build an evidence ledger before the staged minutes
writer runs. It should not be treated as the final writer.

## Train

```bash
cd /root/meeting-minutes-evidence-model
python3 scripts/train_evaluate.py --data data/training_data.csv --schema labels/status_schema.json --output runs/first-pass-YYYYMMDD/model_bundle --splits 4
```

## Predict

```bash
python3 scripts/predict.py --model runs/first-pass-YYYYMMDD/model_bundle/classifier.joblib "Orla will review the QMS manual by Tuesday."
```

## Probe a transcript

```bash
python3 scripts/probe_transcript.py --model runs/first-pass-YYYYMMDD/model_bundle/classifier.joblib --text-file /tmp/transcript.txt
```

