Dan Stillman ddeaefdbe0 Replace the best-match top-K cutoff with a ranked Relevance column ... Semantic similarity has no natural relevance threshold, so instead of asking the user to pick an arbitrary result count, show every scored item and surface the ranking directly: a Relevance column appears and becomes the sort while a best-match search is active, and the previous sort and columns return when it clears. The merged results are scored in a single pass in the row provider, so ranks are global across a multi-collection selection, child items (attachments, notes, annotations) rank via their top-level item, and equal scores get equal ranks that order deterministically via the secondary sort fields. Items without a stored embedding are filtered out. Each cell renders the score's position within the model's display range as a bar, so relevant results read as full and the irrelevant tail reads as empty. The ranges are provisional per-model display constants. Sorting uses the ranks, which are also exposed to assistive technology and as the cell tooltip. On a focused selected row the bar switches to white so the fill doesn't vanish into the accent selection background.		2026-10-08 15:10:24 -07:00
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preferences	Replace the best-match top-K cutoff with a ranked Relevance column	2026-10-08 15:10:24 -07:00