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/api/admin_recommendation_tuning.go

@@ -20,26 +20,28 @@ import (
 // weightsResp is one weight profile on the wire, keyed by the same
 // snake_case field names the PATCH body accepts.
 type weightsResp struct {
-	BaseWeight       float64 `json:"base_weight"`
-	LikeBoost        float64 `json:"like_boost"`
-	RecencyWeight    float64 `json:"recency_weight"`
-	SkipPenalty      float64 `json:"skip_penalty"`
-	JitterMagnitude  float64 `json:"jitter_magnitude"`
-	ContextWeight    float64 `json:"context_weight"`
-	SimilarityWeight float64 `json:"similarity_weight"`
-	TasteWeight      float64 `json:"taste_weight"`
+	BaseWeight        float64 `json:"base_weight"`
+	LikeBoost         float64 `json:"like_boost"`
+	RecencyWeight     float64 `json:"recency_weight"`
+	SkipPenalty       float64 `json:"skip_penalty"`
+	JitterMagnitude   float64 `json:"jitter_magnitude"`
+	ContextWeight     float64 `json:"context_weight"`
+	SimilarityWeight  float64 `json:"similarity_weight"`
+	TasteWeight       float64 `json:"taste_weight"`
+	ContextTimeWeight float64 `json:"context_time_weight"`
 }
 
 func weightsRespFrom(w recommendation.ScoringWeights) weightsResp {
 	return weightsResp{
-		BaseWeight:       w.BaseWeight,
-		LikeBoost:        w.LikeBoost,
-		RecencyWeight:    w.RecencyWeight,
-		SkipPenalty:      w.SkipPenalty,
-		JitterMagnitude:  w.JitterMagnitude,
-		ContextWeight:    w.ContextWeight,
-		SimilarityWeight: w.SimilarityWeight,
-		TasteWeight:      w.TasteWeight,
+		BaseWeight:        w.BaseWeight,
+		LikeBoost:         w.LikeBoost,
+		RecencyWeight:     w.RecencyWeight,
+		SkipPenalty:       w.SkipPenalty,
+		JitterMagnitude:   w.JitterMagnitude,
+		ContextWeight:     w.ContextWeight,
+		SimilarityWeight:  w.SimilarityWeight,
+		TasteWeight:       w.TasteWeight,
+		ContextTimeWeight: w.ContextTimeWeight,
 	}
 }