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/recommendation/score.go

@@ -19,6 +19,11 @@ type ScoringInputs struct {
 	SkipCount            int        // play_events with was_skipped=true
 	ContextualMatchScore float64    // [0, 1]; 0 when no signal
 	SimilarityScore      float64    // [0, 1]; 0 when no signal (random fill)
+	// TasteMatchScore is the candidate's fit to the user's learned taste
+	// profile (#796 phase 2), in [-1, +1]: positive draws a track toward the
+	// user's taste, negative reflects passive avoidance, 0 when there's no
+	// profile signal (cold start / artist+tags absent from the profile).
+	TasteMatchScore float64
 }
 
 // ScoringWeights are the operator-tunable knobs. Defaults live in
@@ -31,6 +36,7 @@ type ScoringWeights struct {
 	JitterMagnitude  float64
 	ContextWeight    float64
 	SimilarityWeight float64
+	TasteWeight      float64
 }
 
 // Score computes the weighted-shuffle score per spec §6:
@@ -41,6 +47,7 @@ type ScoringWeights struct {
 //	      - skip_ratio * SkipPenalty
 //	      + contextual_match_score * ContextWeight
 //	      + similarity_score * SimilarityWeight
+//	      + taste_match_score * TasteWeight
 //	      + small_random_jitter
 //
 // Higher score = more likely to surface. rng is a function returning a
@@ -55,6 +62,7 @@ func Score(in ScoringInputs, w ScoringWeights, now time.Time, rng func() float64
 	s -= skipRatio(in.PlayCount, in.SkipCount) * w.SkipPenalty
 	s += in.ContextualMatchScore * w.ContextWeight
 	s += in.SimilarityScore * w.SimilarityWeight
+	s += in.TasteMatchScore * w.TasteWeight
 	s += (rng()*2 - 1) * w.JitterMagnitude
 	return s
 }