USER_GUIDE.md

How to use EvalFlow CI Lab

Quick start: Open App. Choose Multinomial Naive Bayes as baseline, Hybrid TF-IDF as candidate, and Harder challenge · 54 as split. Click Run release audit. The candidate should show 77.8% Accuracy and the default research policy should return PASS.

• Command Center: see exact metrics and gate results.
• Pipeline Replay: review seven stages and the executable CLI command.
• Paired Regressions: filter repaired examples, newly incorrect examples and changed predictions. Search by example ID or source text.
• Release Gates: try changing minimum Accuracy from 0.75 to 0.95; it should BLOCK. Use reset to return to the documented default.
• Slice Diagnostics: use language/label groupings. The challenge split contains only one mixed domain, shown as a warning. For domain slices, use the controlled IID split.
• Robustness Checks: inspect typo/context flip rates and example coverage. Truncation is destructive and not scored.
• Run Registry: downloads are essential because browser sessions are not persisted.
• CI Integration: instructions to activate the optional workflow on GitHub.
• Export & Provenance: download CSV, JSON and Markdown. Custom evaluation JSON stays in the browser and is marked unverified. Restore original dataset anytime.