feat(documents): PR-Chore-OCR-Column-1 add ocr_derived column

RAG-independent data hygiene. ocr_derived 식별 컬럼 부재 = PR-Eval-V0_2
TBD-O FAILED 원인. 향후 OCR/Marker Diagnose, markdown 품질 분류,
ingest 품질 통계 어디에서나 재사용 가능.

Schema: documents.ocr_derived BOOLEAN NOT NULL DEFAULT false.
Backfill rule R1 단독 (실측 audit 후): extract_meta ? ocr_attempted
AND ocr_attempted = true. 8 rows true / 21727 false.

R2 (file_format IN png/jpg) 폐기 — 1건 R1 흡수 + 1건 marker 미처리.
R3 (marker PDF extract_meta 부재 283 rows) 폐기 — born-digital
false positive 위험. UPDATE 전 candidate preview + source rule별
count + 표본 audit gate 통과 후 적용.

asyncpg single-statement 제약으로 ALTER (277) + UPDATE (278) 분리.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

app/models/document.py

@@ -35,6 +35,7 @@ class Document(Base):
 
     # 2계층: 추출 메타 (OCR 판정/실행)
     extract_meta: Mapped[dict | None] = mapped_column(JSONB, default=dict)
+    ocr_derived: Mapped[bool] = mapped_column(Boolean, nullable=False, default=False)
 
     # 2계층: AI 가공
     ai_summary: Mapped[str | None] = mapped_column(Text)