refactor(discover): both affinities weigh a watch by one rule

The YouTube channel affinity and the Plex one each had the recency decay, the undated-watch rule and
the scale to the strongest; app.draw now holds them. Tests hold that another user's history leans
neither draw, the rail's blind slot, and that a show leans on show recommendations.

backend/app/discover/queries.py

@@ -77,7 +77,8 @@ _FEED_BASE: dict = {
 
 
 def _seeded(col, seed: int):
-    """The feed's deterministic shuffle expression, reused for Plex so one seed moves both halves."""
+    """The Home surprise's seeded order (md5 of the key and the seed), the same for Plex so one
+    seed moves both halves."""
     return func.md5(func.concat(col, str(seed)))
 
 
@@ -188,14 +189,9 @@ def _channel_affinity(db: Session, user: User) -> dict[str, float]:
     now = datetime.now(timezone.utc)
     scores: dict[str, float] = {}
     for channel_id, watched_at in rows:
-        age = (
-            (now - watched_at).total_seconds() / 86400 if watched_at else 2 * WATCHED_HALF_LIFE_DAYS
-        )
-        scores[channel_id] = scores.get(channel_id, 0.0) + 0.5 ** (
-            max(0.0, age) / WATCHED_HALF_LIFE_DAYS
-        )
-    top = max(scores.values(), default=0.0)
-    return {k: v / top for k, v in scores.items()} if top else {}
+        r = draw.recency(watched_at, now, WATCHED_HALF_LIFE_DAYS)
+        scores[channel_id] = scores.get(channel_id, 0.0) + r
+    return draw.scaled(scores)
 
 
 def yt_video_row(db: Session, user: User, video_id: str) -> dict | None: