feat: split unmatched listening by whether the library holds the title

"Unmatched by an artist the library holds" was presented as the matcher's
misses. On real data it is not: owning one album by an artist says nothing about
owning a particular single of theirs, and most of that figure turned out to be
drum and bass tracks streamed but never bought.

Split it in two. A title the library holds under some other artist is an
attribution disagreement -- a remixer credited as the artist, a guest billed as
one -- and is a genuine miss worth fixing; the report now names the artist the
library files it under, which is the information needed to judge it. A title the
library does not hold at all under any artist was never bought, and no
improvement to matching will conjure it.

The distinction matters beyond presentation. That figure is the gate on the
cull, and a gate computed from a number that overstates the failure rate blocks
work that is actually safe to do.

music_curator.py

@@ -1119,12 +1119,55 @@ def coverage_report(store):
         "   AND EXISTS (SELECT 1 FROM lidarr_artist a WHERE a.norm_name = k.norm_artist)"
     ).fetchone()
     logger.info(
-        "unmatched by an artist the library holds: %d pairs, %d plays -- these are the"
-        " matcher's misses, not music you do not own",
+        "unmatched by an artist the library holds: %d pairs, %d plays",
         suspect["pairs"],
         suspect["plays"],
     )
 
+    # Owning an artist is a weak proxy for owning a track, so that figure alone
+    # overstates the matcher's failings. Split it. A title the library holds
+    # under some other artist is an attribution disagreement -- a remixer
+    # credited as the artist, a guest billed as one -- and is a real miss. A
+    # title the library does not hold at all was simply never bought, and no
+    # amount of matching will conjure it.
+    attribution = store.connection.execute(
+        "SELECT COUNT(*) AS pairs, COALESCE(SUM(plays), 0) AS plays FROM scrobble_key k"
+        " WHERE k.track_id IS NULL"
+        "   AND EXISTS (SELECT 1 FROM lidarr_artist a WHERE a.norm_name = k.norm_artist)"
+        "   AND EXISTS (SELECT 1 FROM lidarr_track t WHERE t.norm_title = k.norm_track)"
+    ).fetchone()
+    logger.info(
+        "  of those, the title exists under another artist: %d pairs, %d plays"
+        " -- attribution disagreements, and the genuine misses",
+        attribution["pairs"],
+        attribution["plays"],
+    )
+    logger.info(
+        "  the rest, %d pairs, %d plays: you own the artist but not the track",
+        suspect["pairs"] - attribution["pairs"],
+        suspect["plays"] - attribution["plays"],
+    )
+
+    mismatched = store.connection.execute(
+        "SELECT k.artist, k.track, k.plays,"
+        "       (SELECT a.name FROM lidarr_track t"
+        "          JOIN lidarr_artist a ON a.id = t.artist_id"
+        "         WHERE t.norm_title = k.norm_track LIMIT 1) AS filed_under"
+        "  FROM scrobble_key k"
+        " WHERE k.track_id IS NULL"
+        "   AND EXISTS (SELECT 1 FROM lidarr_artist a WHERE a.norm_name = k.norm_artist)"
+        "   AND EXISTS (SELECT 1 FROM lidarr_track t WHERE t.norm_title = k.norm_track)"
+        " ORDER BY k.plays DESC, k.artist LIMIT 10"
+    ).fetchall()
+    for position, row in enumerate(mismatched, start=1):
+        logger.info(
+            "  attribution %2d: %-45s %4d plays, filed under %s",
+            position,
+            f"{row['artist']} - {row['track']}"[:45],
+            row["plays"],
+            row["filed_under"],
+        )
+
     with_files = store.scalar("SELECT COUNT(*) FROM lidarr_track WHERE has_file = 1")
     played = store.scalar(
         "SELECT COUNT(DISTINCT k.track_id) FROM scrobble_key k"