feat(ml): CCIP references exclude unconfirmed auto character tags + confirm trips detectors (m139)

Completes "no self-training": unconfirmed auto-applied character tags no longer
seed CCIP references — character_references + the prototype builder
(_current_fingerprints/_rebuild_one) gain a shared _positive_char_tag filter
(human-applied OR operator-confirmed), mirroring the head-positive exclusion.

Confirming a tag also has to move the change-detectors, or an incremental
refresh/Retrain right after a confirm wouldn't fold the tag in (only the nightly
full pass would): the CCIP global gate now counts character confirmations, and
the head training fingerprint counts confirmations. Test for the CCIP path.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01CDgx8bQS5YrGRK76v8HUnM

backend/app/services/ml/heads.py

@@ -189,11 +189,20 @@ def _head_fingerprints(session: Session, tag_ids: list[int]) -> dict[int, str]:
         .group_by(TagSuggestionRejection.tag_id)
     ).all()
     rej_map = {t: (c, m) for t, c, m in rej}
+    # Confirmations promote an auto-applied tag to a positive (milestone 139), so
+    # a confirm must move the fingerprint too — else a manual Retrain right after
+    # confirming wouldn't fold the tag in (the nightly full run would).
+    conf = session.execute(
+        select(TagPositiveConfirmation.tag_id, func.count())
+        .where(TagPositiveConfirmation.tag_id.in_(tag_ids))
+        .group_by(TagPositiveConfirmation.tag_id)
+    ).all()
+    conf_map = {t: c for t, c in conf}
     out = {}
     for t in tag_ids:
         pc, pm = pos_map.get(t, (0, None))
         rc, rm = rej_map.get(t, (0, None))
-        out[t] = f"{pc}:{pm}:{rc}:{rm}"
+        out[t] = f"{pc}:{pm}:{rc}:{rm}:{conf_map.get(t, 0)}"
     return out