feat(taste): time-of-day / weekday context conditioning — #1531

Milestone #160 Opt 3 (temporal half). A new additive scoring term that
boosts a candidate when its artist's play history concentrates in the
CURRENT daypart × weekday-type cell, in the user's local timezone.

- Migration 0046: recommendation_weight_profiles.context_time_weight
  (per-profile scoring weight, DEFAULT 1.0).
- Query ListArtistContextPlayCountsForUser: per-artist completed-play
  counts split by the current cell (daypart night[22,5)/morning[5,12)/
  afternoon[12,17)/evening[17,22) × weekday-vs-weekend) via
  started_at AT TIME ZONE users.timezone; 365-day window, skips excluded.
- internal/recommendation/context.go: LoadContextAffinity computes each
  artist's shrunk cell-share minus the user's baseline share, clamped to
  [-1,1]; sparse artists shrink toward baseline (pseudo-count 5), unknown
  artists → 0 (cold-start neutral).
- Score() gains context_affinity_score · ContextTimeWeight; both
  candidate loaders set it per candidate.
- Tuning lab: ContextTimeWeight threaded through recsettings + admin API
  + web card ("Time-of-day weight" row) + Go/web tests. Shipped 1.0 both
  profiles (uniform start, re-bakeable).

Device-class axis deferred to #1551 (needs a client_id → device-class
mapping that doesn't exist yet).

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

internal/recommendation/score.go

@@ -24,19 +24,26 @@ type ScoringInputs struct {
 	// user's taste, negative reflects passive avoidance, 0 when there's no
 	// profile signal (cold start / artist+tags absent from the profile).
 	TasteMatchScore float64
+	// ContextAffinityScore is the candidate artist's time-of-day/weekday
+	// affinity for the CURRENT context (#1531), in [-1, +1]: positive when the
+	// artist's plays concentrate in the current daypart × weekday-type cell
+	// more than the user's baseline, negative when under-represented, 0 when
+	// there's no history (cold-start neutral).
+	ContextAffinityScore float64
 }
 
 // ScoringWeights are the operator-tunable knobs. Defaults live in
 // config.RecommendationConfig and are propagated here per request.
 type ScoringWeights struct {
-	BaseWeight       float64
-	LikeBoost        float64
-	RecencyWeight    float64
-	SkipPenalty      float64
-	JitterMagnitude  float64
-	ContextWeight    float64
-	SimilarityWeight float64
-	TasteWeight      float64
+	BaseWeight        float64
+	LikeBoost         float64
+	RecencyWeight     float64
+	SkipPenalty       float64
+	JitterMagnitude   float64
+	ContextWeight     float64
+	SimilarityWeight  float64
+	TasteWeight       float64
+	ContextTimeWeight float64
 }
 
 // Score computes the weighted-shuffle score per spec §6:
@@ -48,6 +55,7 @@ type ScoringWeights struct {
 //	      + contextual_match_score * ContextWeight
 //	      + similarity_score * SimilarityWeight
 //	      + taste_match_score * TasteWeight
+//	      + context_affinity_score * ContextTimeWeight
 //	      + small_random_jitter
 //
 // Higher score = more likely to surface. rng is a function returning a
@@ -63,6 +71,7 @@ func Score(in ScoringInputs, w ScoringWeights, now time.Time, rng func() float64
 	s += in.ContextualMatchScore * w.ContextWeight
 	s += in.SimilarityScore * w.SimilarityWeight
 	s += in.TasteMatchScore * w.TasteWeight
+	s += in.ContextAffinityScore * w.ContextTimeWeight
 	s += (rng()*2 - 1) * w.JitterMagnitude
 	return s
 }