Six-model clipboard semantics baseline

This directory preserves the complete evaluation report that was deployed before the three new intent classifiers were added. It is a metrics baseline, not a second set of deployable model binaries.

Report generated at: 2026-08-22T09:30:13Z
Corpus records: 7,272
Models: task, question, invitation, complaint, replyableMessage, sentiment
Manifest schema: 1
Report SHA-256: eaa3c2c3fe4151bd6585bfbe7404f848543e4b7321d9ba4376b9c872d2844fdd

The original deployment manifest used these global thresholds:

task: 0.60
question: 0.60
invitation: 0.77
complaint: 0.68
replyableMessage: 0.60
sentiment: no binary threshold

Deployed asset SHA-256 values:

443ce5406a14e3b2051fb265caec116025ee8db088eff496dadb337535843b24  ComplaintIntentClassifier.mlmodel
b7e2266e0926daa9b37926170da200b150024edc55c6bd7644f4252ecaead07c  ConversationalReplyIntentClassifier.mlmodel
e3b9391a5349a43eea511c2e3c7a6697f350510532dc4f190ef707a871a86125  InvitationIntentClassifier.mlmodel
eb0f57da2ea17abcb3847d7c318feb3f50fd0393ffd2ec57c93d9d59bc583dc3  QuestionIntentClassifier.mlmodel
3c7c849cb00163ae0b17d9444f2359aa5f1aecb6d9d65a945b91e9f1d09f9b6d  SentimentClassifier.mlmodel
e4f465e1b62da6ad916e3af1be10d1c63487865134857145476143499af408db  TaskIntentClassifier.mlmodel
722047dbe2df7d4f73d3f7d75cd8fbd9a05e47cb7fa5ec71cab2981a5b91c6ac  clipboard-semantic-models.json

See evaluation-report.json in this directory for every aggregate, per-language, and error-example metric from the baseline run.