feat(ml): drop image_record.tagger_predictions — image_prediction is sole store (#768 step 3)

Read cutover verified in prod (suggestions + allowlist read image_prediction;
backfill complete at 908k rows / 51k images). Removes the old JSON column and
everything that fed it:

- ImageRecord.tagger_predictions column removed; migration 0046 DROPs it.
  tagger_model_version kept as the "tagged / current?" signal the backfill
  sweep reads (needs-tagging check switched to tagger_model_version IS NULL).
- tag_and_embed no longer dual-writes the JSON — image_prediction is the only
  write path.
- importer re-import reset drops the JSON line (image_prediction rows are
  already deleted on re-import).
- Retired the one-time #768 backfill task + the #764 prune task, their admin
  endpoints, and their Maintenance cards (Backfill/PrunePredictionsCard).
- Tests seed/assert via image_prediction; stale column refs removed.

Disk reclaim is NOT automatic: DROP COLUMN is a catalog change. Run
`VACUUM FULL image_record` off-hours afterward to return the ~100 GB to the OS
so DB backups go small (#739). image_prediction (~90 MB) stays in pg_dump — it's
the source of truth now.

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

alembic/versions/0046_drop_tagger_predictions.py

@@ -0,0 +1,43 @@
+"""drop image_record.tagger_predictions (predictions normalized to image_prediction)
+
+Final step of #768. The per-tag predictions now live in the image_prediction
+table (backfilled from the JSON, read by suggestions + allowlist, written by
+tag_and_embed). The old JSON column is dead weight — and it's the ~100 GB of
+sub-0.70 score tail that bloated image_record's TOAST and broke DB backups
+(#739). Dropping it is a fast catalog change; it does NOT reclaim the disk on
+its own — run `VACUUM FULL image_record` (or pg_repack) afterward, off-hours,
+to return the space to the OS so backups go small.
+
+DROP COLUMN needs a brief ACCESS EXCLUSIVE lock on image_record; env.py's
+lock_timeout guards it, so quiesce the ml-worker if a tagging run is in flight
+(see the migration-lock reference). tagger_model_version is kept — it's the
+"has this been tagged / is it current?" signal the backfill sweep reads.
+
+Revision ID: 0046
+Revises: 0045
+Create Date: 2026-06-11
+
+"""
+from typing import Sequence, Union
+
+import sqlalchemy as sa
+from alembic import op
+
+revision: str = "0046"
+down_revision: Union[str, None] = "0045"
+branch_labels: Union[str, Sequence[str], None] = None
+depends_on: Union[str, Sequence[str], None] = None
+
+
+def upgrade() -> None:
+    op.drop_column("image_record", "tagger_predictions")
+
+
+def downgrade() -> None:
+    # Re-add the column empty. The JSON data is not restored (it lived only in
+    # this column); a downgrade would re-tag or backfill from image_prediction
+    # separately if ever needed.
+    op.add_column(
+        "image_record",
+        sa.Column("tagger_predictions", sa.JSON(), nullable=True),
+    )