feat(wip): soft title tier — sketch/doodle vocab + ring-loud audit (#1474)

Extends WIP title-tagging to lower-precision cues (sketch/doodle/scribble) safely.

- wip_title.py: soft matcher (word-anchored; sketchbook/kadoodle don't trip it);
  WIP_TITLE_SOFT_SOURCE + soft SQL prefilter; apply_wip_image_tags takes a source arg.
- training_data._AUTO_SOURCES += 'wip_title_soft' → the soft tier is PROVISIONAL and
  never trains the wip head (a finished "sketch" can't pollute it). Only the hard
  tier (wip_title) + manual train.
- ImportSettings.wip_soft_title_tagging_enabled (OFF by default, opt-in). Migration 0087.
- importer: hard tier wins, soft is the fallback (source wip_title_soft).
- backfill: refactored into a shared _backfill_wip_tier; hard always, soft when enabled.
- heads.soft_wip_conflict_audit + daily beat: score soft-tagged images against content
  heads, flag ring-loud ones (PresentationReview mode=process) for the review strip —
  the operator's "measure if they got falsely tagged" safety.
- api settings toggle; ImportFiltersForm soft toggle.
- tests: soft matcher pos/neg; soft source not a training positive; audit flags
  ring-loud + spares quiet.

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

backend/app/celery_app.py

@@ -179,6 +179,11 @@ def make_celery() -> Celery:
                 "schedule": 86400.0,  # auto-tag wip/editor process art (#1464);
                 # no-op unless process_auto_apply_enabled (opt-in)
             },
+            "soft-wip-conflict-audit-daily": {
+                "task": "backend.app.tasks.ml.scheduled_soft_wip_conflict_audit",
+                "schedule": 86400.0,  # flag ring-loud soft-WIP (sketch/doodle) tags
+                # for review (#1474); no-op with no content heads
+            },
             "prune-presentation-reviews-daily": {
                 "task": "backend.app.tasks.ml.prune_presentation_reviews",
                 "schedule": 86400.0,  # retention: drop resolved review flags >30d