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The validation/annotation mode toggle previously required both manual annotations AND auto-classifications to exist. Now it appears whenever auto-classification data is available, allowing users to switch to annotation mode for auto-classified-only samples by creating blank annotations on the fly. The session cache now stores/restores the toggle state so it persists across sample switches.
…ments - Add "SQLite → MATLAB ZIP" export via iRfcb::ifcb_zip_matlab() with features/data folder inputs, recursive options, and README metadata - Add IFCB instrument multi-select filter to both ZIP and MATLAB ZIP export dialogs - Scan local classifier files (CSV/H5/MAT) in dashboard mode when dashboard auto-classifications are disabled, showing correct classified status in sample dropdown - Fix Python environment detection by setting RETICULATE_PYTHON before initialization so py_discover_config() resolves to the correct venv - Guard local classifier file loading with dashboard_autoclass check to prevent unintended fallback when dashboard auto-classifications enabled - Show in-app notification when dashboard auto-classification download fails instead of console-only warning - Fix session cleanup handler reading annotator/class2use after session end - Add tests for samples parameter filtering and dashboard classifier scanning - Update vignettes, FAQ, and NEWS with new features
Dashboard class_scores CSV files are served from dataset-specific paths (e.g., /mvco/) rather than the generic /data/ endpoint. Added resolve_sample_dataset() to auto-detect the dataset via the bin API when not provided in the URL. Also fixed "No ROI dimensions available" error when switching from validation to annotation mode in dashboard mode by checking the dashboard PNG cache for dimension inference.
…tation mode Cache validation-mode classifications (e.g. dashboard autoclass) before switching to annotation mode so they can be restored when switching back, instead of showing "No classification data available".
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