feat(taste): phase 2a — apply the taste profile via a TasteMatch scoring term (#796)

The profile built in phase 1 now changes what gets surfaced. Adds a TasteMatch
term to the weighted-shuffle score so candidates are re-ranked by their fit to
the user's learned taste (positive draws toward it; negative reflects passive
avoidance; 0 at cold start).

- recommendation/score.go: ScoringInputs.TasteMatchScore ([-1,+1]) +
  ScoringWeights.TasteWeight + the term in Score.
- recommendation/taste.go: LoadTasteProfile reads the taste_profile_* tables;
  TasteProfile.Match blends the candidate's artist weight (0.7) and avg genre-tag
  weight (0.3), each tanh-squashed by a fixed scale so one outlier artist can't
  compress the rest. Unknown artist/tags and empty profiles → 0 (neutral).
- candidates.go: both candidate loaders set TasteMatchScore per candidate, so
  every Score caller (system playlists incl. You-might-like, radio) becomes
  taste-aware automatically.
- weights: systemMixWeights.TasteWeight = 1.5 (daily mixes are the primary
  taste surface); config.RecommendationConfig gains taste_weight (default 1.0,
  lighter — radio is seed-directed) wired into the radio handler.
- tests: pure (Match curve incl. saturation/clamp/empty-neutral, Score term
  add+subtract) + DB round-trip (seed taste rows → Match positive). All green
  vs real Postgres; existing playlist/radio tests unaffected (empty profile →
  zero taste effect).

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

internal/playlists/system.go

@@ -148,6 +148,11 @@ var systemMixWeights = recommendation.ScoringWeights{
 	JitterMagnitude:  0.1,
 	ContextWeight:    0.5,
 	SimilarityWeight: 1.5,
+	// Taste profile (#796 phase 2): the daily mixes are the primary
+	// taste-driven surface, so they lean on it. TasteMatchScore is in
+	// [-1,+1], so 1.5 makes a strong taste fit comparable to a like boost
+	// while passive avoidance (negative) gently demotes.
+	TasteWeight: 1.5,
 }
 
 // forYouHeadN is the number of top-scored tracks that anchor the For-You