diff --git a/app/api/study_topics.py b/app/api/study_topics.py
index a4da1be..ace0b85 100644
--- a/app/api/study_topics.py
+++ b/app/api/study_topics.py
@@ -1805,6 +1805,35 @@ async def get_quiz_session(
     ]
 
     summary = await _build_session_summary(qs, session, include_progress_counts=True)
+
+    # Phase 4-A: 결과 화면 GET fallback — finalize enqueue 누락 또는 worker 처리 전
+    # 사용자가 결과 들어온 경우 같은 wrong/unsure qid 를 idempotent backfill enqueue.
+    # 한 요청당 30 cap + non-blocking + debug 로그. 실패해도 GET 200 유지.
+    if qs.status == "done":
+        try:
+            from services.study.explanation_enqueue import enqueue_explanation_for_qids
+            wrong_unsure_qids = [
+                a.study_question_id for a in attempt_rows
+                if a.outcome in ("wrong", "unsure")
+            ]
+            if wrong_unsure_qids:
+                res = await enqueue_explanation_for_qids(
+                    session,
+                    user_id=user.id,
+                    qids=wrong_unsure_qids,
+                    max_count=30,  # GET fallback cap
+                )
+                await session.commit()
+                logger.debug(
+                    "phase4a_get_backfill session=%s candidates=%s enqueued=%s skipped=%s",
+                    qs.id, res["candidate_count"], res["enqueue_count"], res["skipped_count"],
+                )
+        except Exception as e:
+            logger.warning(
+                "phase4a_get_backfill_failed session=%s: %s: %s",
+                qs.id, type(e).__name__, e,
+            )
+
     return QuizSessionDetailResponse(
         summary=summary,
         questions=questions_payload,
diff --git a/app/main.py b/app/main.py
index cdca5f7..3cec1ce 100644
--- a/app/main.py
+++ b/app/main.py
@@ -44,6 +44,7 @@ async def lifespan(app: FastAPI):
     from workers.mailplus_archive import run as mailplus_run
     from workers.news_collector import run as news_collector_run
     from workers.queue_consumer import consume_queue
+    from workers.study_queue_consumer import consume_study_queue
     from workers.study_question_embed_worker import (
         refresh_stale_related as study_q_related_refresh,
         run as study_q_embed_run,
@@ -75,6 +76,9 @@ async def lifespan(app: FastAPI):
     # PR-12-A 후속: related-types 캐시 stale 행 재계산. 임베딩 워커와 분리한 별도 cron.
     # 새 문제 ready / 같은 토픽 invalidation / 임계값 변경 시 NULL 마킹된 행을 batch=20 처리.
     scheduler.add_job(study_q_related_refresh, "interval", minutes=1, id="study_q_related_refresh")
+    # Phase 4-A: study_question_jobs 처리 — wrong/unsure AI 풀이 prefetch.
+    # MLX gate 직렬화 + BATCH_SIZE=1 로 GPU 부하 통제. STALE_MINUTES=10 자체 복구.
+    scheduler.add_job(consume_study_queue, "interval", minutes=1, id="study_queue_consumer")
     # PR-B 레거시 tier 백필 — 30분 주기로 호출되지만 KST 00:00~06:00 시간대만 실제 enqueue.
     # safety > law > manual 우선순위로 25건씩. 6720 레거시 → 야간당 ~150건 → 약 45일 소화.
     scheduler.add_job(tier_backfill_run, "interval", minutes=30, id="tier_backfill")
diff --git a/app/models/study_question_job.py b/app/models/study_question_job.py
new file mode 100644
index 0000000..e4a321c
--- /dev/null
+++ b/app/models/study_question_job.py
@@ -0,0 +1,87 @@
+"""study_question_jobs ORM (Phase 4-A) — study 도메인 전용 비동기 작업 큐.
+
+processing_queue 가 documents.id FK 라 study_questions 에 직접 재사용 불가.
+별도 테이블 + 별도 consumer (study_queue_consumer.py).
+
+kind 권장값:
+  - 'explanation' (Phase 4-A): wrong/unsure 문제의 AI 풀이 prefetch
+  - 'session_summary' (Phase 4-B 예약): 세션 단위 종합 분석. session_summary 는 question
+    단위에 얹기 어색해 Phase 4-B 구현 시 study_quiz_session_jobs 별도 분리 검토.
+
+terminal status (completed/failed/skipped) 는 completed_at 항상 기록.
+failed 재시도는 기존 row 를 pending 으로 되살리지 않고 새 row 생성 — 이력 누적.
+"""
+
+from __future__ import annotations
+
+from datetime import datetime
+from typing import Any
+
+from sqlalchemy import BigInteger, DateTime, ForeignKey, SmallInteger, String, Text, text
+from sqlalchemy.dialects.postgresql import JSONB, insert as pg_insert
+from sqlalchemy.ext.asyncio import AsyncSession
+from sqlalchemy.orm import Mapped, mapped_column
+
+from core.database import Base
+
+
+class StudyQuestionJob(Base):
+    __tablename__ = "study_question_jobs"
+
+    id: Mapped[int] = mapped_column(BigInteger, primary_key=True)
+    study_question_id: Mapped[int] = mapped_column(
+        BigInteger, ForeignKey("study_questions.id", ondelete="CASCADE"), nullable=False
+    )
+    user_id: Mapped[int] = mapped_column(
+        BigInteger, ForeignKey("users.id", ondelete="CASCADE"), nullable=False
+    )
+    kind: Mapped[str] = mapped_column(String(40), nullable=False)
+    status: Mapped[str] = mapped_column(String(20), nullable=False, default="pending")
+    attempts: Mapped[int] = mapped_column(SmallInteger, nullable=False, default=0)
+    max_attempts: Mapped[int] = mapped_column(SmallInteger, nullable=False, default=2)
+    error_code: Mapped[str | None] = mapped_column(String(40))
+    error_message: Mapped[str | None] = mapped_column(Text)
+    payload: Mapped[dict | None] = mapped_column(JSONB)
+    created_at: Mapped[datetime] = mapped_column(
+        DateTime(timezone=True), default=datetime.now, nullable=False
+    )
+    started_at: Mapped[datetime | None] = mapped_column(DateTime(timezone=True))
+    completed_at: Mapped[datetime | None] = mapped_column(DateTime(timezone=True))
+
+    # active partial unique idx 는 migration 232 가 관리.
+
+
+async def enqueue_study_question_job(
+    session: AsyncSession,
+    *,
+    study_question_id: int,
+    user_id: int,
+    kind: str,
+    payload: dict[str, Any] | None = None,
+) -> bool:
+    """study_question_jobs 에 행 추가 (DB 레벨 중복 방어).
+
+    같은 (study_question_id, kind) 에 활성 행 (pending/processing) 이 이미 있으면
+    아무것도 하지 않고 False 반환. terminal 이력은 별도 row 로 누적되므로 이번 호출이
+    failed/skipped/completed row 와 무관하게 새 active 행을 만들 수 있다.
+
+    Returns: True = 새 enqueue 발생, False = 중복으로 건너뜀.
+    """
+    values: dict[str, Any] = {
+        "study_question_id": study_question_id,
+        "user_id": user_id,
+        "kind": kind,
+        "status": "pending",
+    }
+    if payload is not None:
+        values["payload"] = payload
+    stmt = (
+        pg_insert(StudyQuestionJob)
+        .values(**values)
+        .on_conflict_do_nothing(
+            index_elements=["study_question_id", "kind"],
+            index_where=text("status IN ('pending', 'processing')"),
+        )
+    )
+    result = await session.execute(stmt)
+    return result.rowcount > 0
diff --git a/app/prompts/study_explanation_envelope.txt b/app/prompts/study_explanation_envelope.txt
new file mode 100644
index 0000000..e694c57
--- /dev/null
+++ b/app/prompts/study_explanation_envelope.txt
@@ -0,0 +1,42 @@
+당신은 한국 기사시험(가스기사·산업안전기사 등) 필기 학습 보조 AI 입니다.
+4지선다 객관식 문제를 분석하고 정답 풀이를 작성합니다.
+
+【문제】
+{question_text}
+
+【보기】
+1. {choice_1}
+2. {choice_2}
+3. {choice_3}
+4. {choice_4}
+
+【사용자가 입력한 정답】
+{correct_choice}번
+
+【참고 자료 — 우선순위 순서】
+
+▼ 자료 (1순위: 자료실 매핑 문서)
+{documents_evidence_block}
+
+▼ 같은 주제의 다른 문제 (2순위: 보조 근거)
+{questions_evidence_block}
+
+【지침】
+1. 자료를 1순위 근거로 사용. 다른 문제는 보조 근거로만.
+2. 자료 인용은 [자료: 제목] 형태. 문제 인용은 [관련: Q<id>] 형태.
+3. 정답이 왜 맞는지 핵심 개념 → 오답 보기가 왜 틀렸는지 짧게 → 정리 순서.
+4. 자료에 직접 근거가 없으면 "자료 근거 부족" 으로 명시하고, 일반 상식 풀이는 별도 단락에 표시.
+5. **할루시네이션 방지 (절대 규칙)**:
+   - 자료 근거가 부족하면 법령명·조항·수치·기준값을 새로 만들어내지 않는다.
+   - 근거 없는 수치(예: "0.5 MPa", "10 mg/L")·공식·표준 번호(예: "KS B 6750")·통계는 작성하지 않는다.
+   - 자료에서 확인되지 않는 내용은 "자료에서 확인되지 않음" 이라고 명시한다.
+   - "보통 ~이다", "일반적으로 ~이다" 같은 모호한 단정도 자료 근거가 없으면 사용하지 않는다.
+6. confidence 는 풀이 근거 강도에 따라 high/medium/low 중 하나로 선택:
+   - high: 자료에 직접 근거가 있고 정답이 명확
+   - medium: 자료가 부분 근거이고 일반 지식 보강 필요
+   - low: 자료 근거 부족하여 추론에 의존
+7. answer_choice 는 풀이의 결론에 해당하는 정답 번호 (1~4 정수). 사용자 입력 정답과 자료 근거가 충돌하면 자료 근거를 따르고 explanation_md 에 충돌을 명시.
+8. explanation_md 는 한국어 200~400자. 마크다운(굵게·리스트) 사용 가능.
+
+【출력 형식 — 반드시 아래 JSON 만 출력. 메타 설명·인사·코드 펜스 없이 raw JSON 한 객체.】
+{{"answer_choice": <1|2|3|4>, "explanation_md": "<풀이 본문 마크다운>", "confidence": "<high|medium|low>"}}
diff --git a/app/services/study/explanation_enqueue.py b/app/services/study/explanation_enqueue.py
new file mode 100644
index 0000000..5e1d551
--- /dev/null
+++ b/app/services/study/explanation_enqueue.py
@@ -0,0 +1,119 @@
+"""Phase 4-A 풀이 prefetch enqueue 헬퍼 — finalize_session + 결과 GET fallback 공유.
+
+대상 조건:
+  - ai_explanation_status IN ('none', 'failed') OR ai_explanation IS NULL
+  - skipped / stale 은 자동 enqueue 대상 X (각각 자료 추가 / 명시 [다시 생성] 트리거)
+  - 같은 (qid, kind='explanation') 의 최신 study_question_jobs.error_code 가
+    guard_fail 또는 evidence_missing 이면 제외 (자동 재시도 금지 사유)
+
+Plan: ~/.claude/plans/nifty-sparking-spindle.md
+"""
+
+from __future__ import annotations
+
+import logging
+from typing import Iterable
+
+from sqlalchemy import or_, select
+from sqlalchemy.ext.asyncio import AsyncSession
+
+from models.study_question import StudyQuestion
+from models.study_question_job import StudyQuestionJob, enqueue_study_question_job
+
+logger = logging.getLogger(__name__)
+
+KIND_EXPLANATION = "explanation"
+NO_AUTO_RETRY_ERROR_CODES = ("guard_fail", "evidence_missing")
+
+
+async def filter_needs_explanation(
+    session: AsyncSession, qids: Iterable[int]
+) -> list[int]:
+    """주어진 qid 중 자동 enqueue 대상만 추려서 반환.
+
+    1차 SQL: study_questions 자체 조건 (status / ai_explanation null)
+    2차 Python: 각 후보의 최신 study_question_jobs error_code 가 자동 재시도 금지 사유면 제외
+    """
+    qids = list(qids)
+    if not qids:
+        return []
+
+    rows = (
+        await session.execute(
+            select(StudyQuestion.id).where(
+                StudyQuestion.id.in_(qids),
+                StudyQuestion.deleted_at.is_(None),
+                or_(
+                    StudyQuestion.ai_explanation_status.in_(("none", "failed")),
+                    StudyQuestion.ai_explanation.is_(None),
+                ),
+                # skipped / stale 은 자동 enqueue 대상 X
+                StudyQuestion.ai_explanation_status.notin_(("skipped", "stale", "ready", "pending")),
+            )
+        )
+    ).scalars().all()
+    candidate_ids = list(rows)
+    if not candidate_ids:
+        return []
+
+    # 각 후보의 최신 job (id DESC) 의 error_code — Python 에서 첫 row 만 채택
+    job_rows = (
+        await session.execute(
+            select(StudyQuestionJob.study_question_id, StudyQuestionJob.error_code)
+            .where(
+                StudyQuestionJob.study_question_id.in_(candidate_ids),
+                StudyQuestionJob.kind == KIND_EXPLANATION,
+            )
+            .order_by(
+                StudyQuestionJob.study_question_id.asc(),
+                StudyQuestionJob.id.desc(),
+            )
+        )
+    ).all()
+    latest_error_by_qid: dict[int, str | None] = {}
+    for r in job_rows:
+        # 같은 qid 의 첫 등장 row = 최신 (id DESC 정렬)
+        if r.study_question_id not in latest_error_by_qid:
+            latest_error_by_qid[r.study_question_id] = r.error_code
+
+    return [
+        qid for qid in candidate_ids
+        if latest_error_by_qid.get(qid) not in NO_AUTO_RETRY_ERROR_CODES
+    ]
+
+
+async def enqueue_explanation_for_qids(
+    session: AsyncSession,
+    *,
+    user_id: int,
+    qids: Iterable[int],
+    max_count: int | None = None,
+) -> dict[str, int]:
+    """주어진 qid 묶음에 대해 enqueue 수행. caller 가 commit 책임.
+
+    max_count: 한 호출에 enqueue 할 최대 행 수 (GET fallback 30 cap).
+    Returns: {'enqueue_count': N, 'skipped_count': M, 'candidate_count': K}
+    """
+    candidates = await filter_needs_explanation(session, qids)
+    if max_count is not None:
+        candidates = candidates[:max_count]
+
+    enqueue_count = 0
+    skipped_count = 0
+    for qid in candidates:
+        ok = await enqueue_study_question_job(
+            session,
+            study_question_id=qid,
+            user_id=user_id,
+            kind=KIND_EXPLANATION,
+        )
+        if ok:
+            enqueue_count += 1
+        else:
+            # 이미 active 행 있어 on_conflict_do_nothing — 정상.
+            skipped_count += 1
+    return {
+        "enqueue_count": enqueue_count,
+        "skipped_count": skipped_count,
+        "candidate_count": len(candidates),
+    }
diff --git a/app/services/study/session_finalize.py b/app/services/study/session_finalize.py
index 4852e5f..1d9b5b8 100644
--- a/app/services/study/session_finalize.py
+++ b/app/services/study/session_finalize.py
@@ -213,6 +213,30 @@ async def finalize_session(
         qs.recovered_count = recovered_count
         qs.chronic_remaining_count = chronic_remaining
 
+    # 6. Phase 4-A: 이 세션의 wrong/unsure qid AI 풀이 prefetch enqueue (best-effort).
+    # 실패가 finalize 자체를 깨뜨리지 않도록 try/except 로 격리. 응답 카운트와 무관.
+    try:
+        from services.study.explanation_enqueue import enqueue_explanation_for_qids
+        wrong_unsure_qids = [
+            qid for qid, a in last_per_qid.items()
+            if a.outcome in ("wrong", "unsure")
+        ]
+        if wrong_unsure_qids:
+            res = await enqueue_explanation_for_qids(
+                session, user_id=user_id, qids=wrong_unsure_qids,
+            )
+            import logging
+            logging.getLogger(__name__).info(
+                "phase4a_finalize_enqueue session=%s candidates=%s enqueued=%s skipped=%s",
+                quiz_session_id, res["candidate_count"], res["enqueue_count"], res["skipped_count"],
+            )
+    except Exception as e:
+        import logging
+        logging.getLogger(__name__).warning(
+            "phase4a_finalize_enqueue_failed session=%s: %s: %s",
+            quiz_session_id, type(e).__name__, e,
+        )
+
     return SessionSummary(
         correct=correct,
         wrong=wrong,
diff --git a/app/workers/study_explanation_worker.py b/app/workers/study_explanation_worker.py
new file mode 100644
index 0000000..a8f20e7
--- /dev/null
+++ b/app/workers/study_explanation_worker.py
@@ -0,0 +1,215 @@
+"""Phase 4-A 풀이 prefetch worker — wrong/unsure 문제의 AI 풀이를 batch 로 미리 생성.
+
+Plan: ~/.claude/plans/nifty-sparking-spindle.md
+study_question_jobs (kind='explanation') row 1건을 받아 처리:
+  1. RAG 근거 수집 (PR-3 의 explanation_rag.py 재사용)
+  2. evidence 둘 다 비어있으면 LLM 호출 X → status='skipped'
+  3. MLX primary 호출 (gate Semaphore(1) 공유) → envelope JSON
+  4. 환각 가드 — answer_choice == question.correct_choice 검증
+  5. 통과 시 study_questions.ai_explanation 캐시 박기
+
+terminal status (completed/failed/skipped) 는 completed_at 항상 기록.
+재시도 정책 — guard_fail/evidence_missing 은 final, 그 외 (llm_timeout/parse_fail/unknown)
+는 attempts < max_attempts 면 pending 으로 복귀.
+"""
+
+from __future__ import annotations
+
+import asyncio
+import json
+import logging
+from datetime import datetime, timezone
+from pathlib import Path
+
+import httpx
+from sqlalchemy.ext.asyncio import AsyncSession
+
+from ai.client import AIClient, parse_json_response
+from models.study_question import StudyQuestion
+from models.study_question_job import StudyQuestionJob
+from services.search.llm_gate import get_mlx_gate
+from services.study.explanation_rag import (
+    gather_explanation_context,
+    render_evidence_block,
+)
+
+logger = logging.getLogger(__name__)
+
+# PR-3 LLM_TIMEOUT_S 와 동일 안전 마진 (26B 평균 ~10s, gate 직렬화 고려)
+LLM_TIMEOUT_S = 30.0
+
+_ENVELOPE_PROMPT_FILE = "study_explanation_envelope.txt"
+_envelope_template_cache: str | None = None
+
+
+def _load_envelope_prompt() -> str:
+    global _envelope_template_cache
+    if _envelope_template_cache is None:
+        prompts_dir = Path(__file__).resolve().parent.parent / "prompts"
+        _envelope_template_cache = (
+            prompts_dir / _ENVELOPE_PROMPT_FILE
+        ).read_text(encoding="utf-8")
+    return _envelope_template_cache
+
+
+def _render_envelope_prompt(q: StudyQuestion, doc_block: str, q_block: str) -> str:
+    return (
+        _load_envelope_prompt()
+        .replace("{question_text}", q.question_text or "")
+        .replace("{choice_1}", q.choice_1 or "")
+        .replace("{choice_2}", q.choice_2 or "")
+        .replace("{choice_3}", q.choice_3 or "")
+        .replace("{choice_4}", q.choice_4 or "")
+        .replace("{correct_choice}", str(q.correct_choice))
+        .replace("{documents_evidence_block}", doc_block)
+        .replace("{questions_evidence_block}", q_block)
+    )
+
+
+async def run_explanation_job(session: AsyncSession, job: StudyQuestionJob) -> None:
+    """Phase 4-A: study_question_jobs row 1건 처리. caller 가 commit 책임.
+
+    job.status 는 호출 전 'pending' 가정. 종료 시 completed/failed/skipped/pending(재시도)
+    중 하나.
+    """
+    now = lambda: datetime.now(timezone.utc)  # noqa: E731
+
+    # attempt + processing 단정
+    job.attempts += 1
+    job.status = "processing"
+    job.started_at = now()
+    await session.flush()
+
+    try:
+        question = await session.get(StudyQuestion, job.study_question_id)
+        if question is None or question.deleted_at is not None:
+            # 삭제된 문제 — job 도 skipped 로 종결.
+            job.error_code = "evidence_missing"
+            job.error_message = "question deleted or missing"
+            job.status = "skipped"
+            job.completed_at = now()
+            return
+
+        # race-safe — PR-3 실시간 호출이 이미 ready 박았으면 즉시 종결.
+        if question.ai_explanation_status == "ready":
+            job.status = "completed"
+            job.completed_at = now()
+            return
+
+        # 1. RAG 근거 수집
+        ctx = await gather_explanation_context(session, job.user_id, question)
+        if not ctx.documents and not ctx.questions:
+            # evidence 없음 — LLM 호출 X. job/question 둘 다 skipped 통일.
+            job.error_code = "evidence_missing"
+            job.error_message = "no document/question evidence in this topic"
+            job.status = "skipped"
+            job.completed_at = now()
+            question.ai_explanation_status = "skipped"
+            question.updated_at = now()
+            return
+
+        # 2. 프롬프트 + MLX primary
+        doc_block = render_evidence_block(ctx.documents)
+        q_block = render_evidence_block(ctx.questions)
+        prompt = _render_envelope_prompt(question, doc_block, q_block)
+
+        ai_client = AIClient()
+        try:
+            async with get_mlx_gate():
+                async with asyncio.timeout(LLM_TIMEOUT_S):
+                    raw_text = await ai_client.call_primary(prompt)
+            primary_name = (
+                ai_client.ai.primary.model
+                if hasattr(ai_client.ai, "primary") and hasattr(ai_client.ai.primary, "model")
+                else "primary"
+            )
+        finally:
+            await ai_client.close()
+
+        if not raw_text or not raw_text.strip():
+            # 빈 응답도 timeout 류로 처리 — 재시도 후보.
+            job.error_code = "llm_timeout"
+            job.error_message = "empty response from primary"
+            return
+
+        # 3. envelope 파싱
+        envelope = parse_json_response(raw_text)
+        if envelope is None or not isinstance(envelope, dict):
+            job.error_code = "parse_fail"
+            job.error_message = "envelope JSON parse failed"
+            return
+
+        answer_choice = envelope.get("answer_choice")
+        explanation_md = envelope.get("explanation_md") or ""
+        confidence = envelope.get("confidence")
+
+        if not isinstance(answer_choice, int) or answer_choice not in (1, 2, 3, 4):
+            job.error_code = "parse_fail"
+            job.error_message = f"invalid answer_choice: {answer_choice!r}"
+            return
+        if not explanation_md.strip():
+            job.error_code = "parse_fail"
+            job.error_message = "empty explanation_md"
+            return
+
+        # 4. 환각 가드 — 정답 번호 일치
+        if answer_choice != question.correct_choice:
+            job.error_code = "guard_fail"
+            job.error_message = (
+                f"answer_choice={answer_choice} != correct_choice={question.correct_choice}"
+            )
+            job.status = "failed"
+            job.completed_at = now()
+            question.ai_explanation_status = "failed"
+            question.updated_at = now()
+            return
+
+        # 5. 성공 — confidence 는 1차 통과 (Phase 4-B 임계 결정).
+        # 운영 분석 자산으로 payload 에 confidence 보존.
+        job_payload = dict(job.payload or {})
+        job_payload["confidence"] = confidence
+        job.payload = job_payload
+
+        question.ai_explanation = explanation_md
+        question.ai_explanation_status = "ready"
+        question.ai_explanation_generated_at = now()
+        question.ai_explanation_model = f"mlx:{primary_name}"
+        question.updated_at = question.ai_explanation_generated_at
+
+        job.status = "completed"
+        job.completed_at = now()
+        return
+
+    except (asyncio.TimeoutError, httpx.HTTPError) as e:
+        job.error_code = "llm_timeout"
+        job.error_message = f"{type(e).__name__}: {e}"
+        logger.warning(
+            "study_explanation_job_timeout job_id=%s qid=%s: %s",
+            job.id, job.study_question_id, e,
+        )
+    except (json.JSONDecodeError, ValueError) as e:
+        job.error_code = "parse_fail"
+        job.error_message = f"{type(e).__name__}: {e}"
+        logger.warning(
+            "study_explanation_job_parse_fail job_id=%s qid=%s: %s",
+            job.id, job.study_question_id, e,
+        )
+    except Exception as e:
+        # 예상 못한 예외 — error_code 미세팅 시 finally 가 None 을 retryable 로 보면 무한 루프.
+        # 명시적으로 'unknown' 박아 재시도 정책 안에 들어가게.
+        job.error_code = "unknown"
+        job.error_message = f"{type(e).__name__}: {e}"
+        logger.exception(
+            "study_explanation_job_unknown_fail job_id=%s qid=%s",
+            job.id, job.study_question_id,
+        )
+    finally:
+        # 재시도 분기 — guard_fail/evidence_missing 은 위 try 에서 이미 단정 종결.
+        # 여기 도달 케이스는 llm_timeout / parse_fail / unknown.
+        if job.status == "processing":
+            retryable = job.error_code in ("llm_timeout", "parse_fail", "unknown")
+            if retryable and job.attempts < job.max_attempts:
+                job.status = "pending"  # 다음 cycle 재시도
+            else:
+                job.status = "failed"
+                job.completed_at = now()
diff --git a/app/workers/study_queue_consumer.py b/app/workers/study_queue_consumer.py
new file mode 100644
index 0000000..6b565e7
--- /dev/null
+++ b/app/workers/study_queue_consumer.py
@@ -0,0 +1,108 @@
+"""Phase 4-A study_question_jobs consumer — APScheduler 1분 간격.
+
+study 도메인 전용 큐 (processing_queue 와 분리). BATCH_SIZE=1 — MLX 26B 가
+deep_summary 와 같은 Semaphore(1) 게이트를 공유하므로 GPU 부하 통제.
+
+stage 별 worker dispatch:
+  - kind='explanation': study_explanation_worker.run_explanation_job (Phase 4-A)
+  - kind='session_summary': Phase 4-B 예약, 1차 미구현 — pending 만 보면 즉시 skipped 처리
+"""
+
+from __future__ import annotations
+
+from datetime import datetime, timedelta, timezone
+
+from sqlalchemy import select, update
+from sqlalchemy.exc import SQLAlchemyError
+
+from core.database import async_session
+from core.utils import setup_logger
+from models.study_question_job import StudyQuestionJob
+from workers.study_explanation_worker import run_explanation_job
+
+logger = setup_logger("study_queue_consumer")
+
+# 한 사이클에 한 row 씩 — MLX 게이트 직렬화 + GPU 부하 예측 가능.
+BATCH_SIZE = 1
+# processing 상태로 STALE_MINUTES 이상 방치된 job 은 worker 가 죽었다고 보고 pending 복구.
+STALE_MINUTES = 10
+
+
+async def reset_stale_study_jobs() -> None:
+    """processing 으로 STALE_MINUTES 이상 방치된 job 을 pending 으로 복구.
+
+    partial unique idx 가 (qid, kind) WHERE status IN ('pending','processing') 이라
+    같은 qid 의 다른 pending 이 동시에 있을 일이 거의 없음 (enqueue 가 on_conflict_do_nothing).
+    그래도 안전하게 update 만 — 충돌 시 IntegrityError 는 단건 단위 catch.
+    """
+    cutoff = datetime.now(timezone.utc) - timedelta(minutes=STALE_MINUTES)
+    try:
+        async with async_session() as session:
+            stmt = (
+                update(StudyQuestionJob)
+                .where(
+                    StudyQuestionJob.status == "processing",
+                    StudyQuestionJob.started_at.is_not(None),
+                    StudyQuestionJob.started_at < cutoff,
+                )
+                .values(status="pending", started_at=None)
+            )
+            result = await session.execute(stmt)
+            await session.commit()
+            n = result.rowcount or 0
+            if n > 0:
+                logger.warning("study_jobs_stale_reset count=%s", n)
+    except SQLAlchemyError as e:
+        logger.exception("study_jobs_stale_reset_failed: %s", e)
+
+
+async def consume_study_queue() -> None:
+    """APScheduler 진입점. pending job BATCH_SIZE 만큼 처리."""
+    await reset_stale_study_jobs()
+
+    async with async_session() as session:
+        rows = (
+            await session.execute(
+                select(StudyQuestionJob)
+                .where(StudyQuestionJob.status == "pending")
+                .order_by(StudyQuestionJob.id.asc())
+                .limit(BATCH_SIZE)
+            )
+        ).scalars().all()
+
+    for job_row in rows:
+        # 각 job 마다 독립 세션 — 한 job 실패가 다른 job 에 전염 X.
+        async with async_session() as s:
+            try:
+                # 같은 row 를 fresh load (lock 회피, 세션 격리)
+                job = await s.get(StudyQuestionJob, job_row.id)
+                if job is None or job.status != "pending":
+                    continue  # 다른 cycle 에서 이미 처리
+
+                if job.kind == "explanation":
+                    await run_explanation_job(s, job)
+                elif job.kind == "session_summary":
+                    # Phase 4-B 미구현 — 즉시 skipped 처리 (lost in queue 방지)
+                    job.status = "skipped"
+                    job.error_code = "unknown"
+                    job.error_message = "session_summary not implemented in Phase 4-A"
+                    job.completed_at = datetime.now(timezone.utc)
+                    logger.info("study_job_unsupported_kind id=%s kind=%s", job.id, job.kind)
+                else:
+                    job.status = "skipped"
+                    job.error_code = "unknown"
+                    job.error_message = f"unknown kind: {job.kind!r}"
+                    job.completed_at = datetime.now(timezone.utc)
+                    logger.warning("study_job_unknown_kind id=%s kind=%s", job.id, job.kind)
+
+                await s.commit()
+                logger.info(
+                    "study_job_processed id=%s qid=%s kind=%s status=%s error_code=%s attempts=%s",
+                    job.id, job.study_question_id, job.kind, job.status, job.error_code,
+                    job.attempts,
+                )
+            except Exception as e:
+                # worker 안에서 잡지 못한 catastrophic 실패 — 세션 rollback 후 다음 cycle 재처리.
+                # study_explanation_worker 가 catch-all except 를 가지므로 여기 도달은 드묾.
+                await s.rollback()
+                logger.exception("study_job_outer_failed job_id=%s: %s", job_row.id, e)
diff --git a/migrations/231_study_question_jobs.sql b/migrations/231_study_question_jobs.sql
new file mode 100644
index 0000000..f3db476
--- /dev/null
+++ b/migrations/231_study_question_jobs.sql
@@ -0,0 +1,24 @@
+-- 231_study_question_jobs.sql
+-- Phase 4-A: study question 도메인 전용 비동기 작업 큐.
+-- processing_queue 가 documents.id FK 라 study_questions 에 직접 재사용 불가.
+--
+-- 라이프사이클:
+--   pending → processing → completed | failed | skipped
+-- terminal status (completed/failed/skipped) 는 completed_at 항상 기록.
+-- failed 재시도는 기존 row 를 pending 으로 되살리지 않고 새 row 생성 — 이력 누적.
+
+CREATE TABLE study_question_jobs (
+    id                  BIGSERIAL    PRIMARY KEY,
+    study_question_id   BIGINT       NOT NULL REFERENCES study_questions(id) ON DELETE CASCADE,
+    user_id             BIGINT       NOT NULL REFERENCES users(id)           ON DELETE CASCADE,
+    kind                VARCHAR(40)  NOT NULL,
+    status              VARCHAR(20)  NOT NULL DEFAULT 'pending',
+    attempts            SMALLINT     NOT NULL DEFAULT 0,
+    max_attempts        SMALLINT     NOT NULL DEFAULT 2,
+    error_code          VARCHAR(40),
+    error_message       TEXT,
+    payload             JSONB,
+    created_at          TIMESTAMPTZ  NOT NULL DEFAULT now(),
+    started_at          TIMESTAMPTZ,
+    completed_at        TIMESTAMPTZ
+);
diff --git a/migrations/232_study_q_jobs_active_uq.sql b/migrations/232_study_q_jobs_active_uq.sql
new file mode 100644
index 0000000..9e28a91
--- /dev/null
+++ b/migrations/232_study_q_jobs_active_uq.sql
@@ -0,0 +1,8 @@
+-- 232_study_q_jobs_active_uq.sql
+-- (study_question_id, kind) 활성 행 중복 차단.
+-- terminal status (completed/failed/skipped) 는 누적 이력이라 unique 대상 X.
+-- 같은 qid 가 failed 후 재enqueue 될 때 새 row 가 들어가는 것을 허용.
+
+CREATE UNIQUE INDEX uq_study_q_jobs_active
+    ON study_question_jobs (study_question_id, kind)
+    WHERE status IN ('pending', 'processing');