\set ON_ERROR_STOP on
\if :{?app_role}
\else
\set app_role vignette
\endif

BEGIN;

INSERT INTO app.app_user (
  user_id, external_id, role, cohort, account_status, consent_at
) VALUES
  ('51000000-0000-0000-0000-000000000001', 'g5-smoke-learner', 'learner', 'g5-smoke', 'approved', now()),
  ('51000000-0000-0000-0000-000000000002', 'g5-smoke-teacher', 'instructor', 'g5-smoke', 'approved', now()),
  ('51000000-0000-0000-0000-000000000003', 'g5-smoke-other', 'learner', 'g5-other', 'approved', now());

INSERT INTO app.sessions (id, learner_id, session_no)
VALUES ('52000000-0000-0000-0000-000000000001', '51000000-0000-0000-0000-000000000001', 1);
INSERT INTO app.turns (id, session_id, seq, speaker, text_masked, actor_kind)
VALUES
  ('53000000-0000-0000-0000-000000000001', '52000000-0000-0000-0000-000000000001', 1, 'counselor', '[G5 masked evidence 1]', 'human_learner'),
  ('53000000-0000-0000-0000-000000000002', '52000000-0000-0000-0000-000000000001', 2, 'client', '[G5 masked evidence 2]', 'client_ai');

INSERT INTO app.measurement_instrument (
  instrument_id, instrument_version, name_ko, instrument_kind,
  construct, validation_basis, scoring_schema, metadata
) VALUES
  (
    'vignette-g5-calibration', '1.0.0', 'G5 역량별 자기보정',
    'training_metric', 'self_calibration',
    '잠긴 자기예측과 독립 관찰의 교육용 역량별 대조.',
    '{"per_competency":true}'::JSONB,
    '{"clinical_claim_allowed":false}'::JSONB
  ),
  (
    'vignette-g5-transfer', '1.0.0', 'G5 미지 사례 전이',
    'training_metric', 'transfer',
    '교육용 합성 미지 사례의 역량별 전이 관찰.',
    '{"per_competency":true,"scenario_novelty":"unseen_transfer"}'::JSONB,
    '{"clinical_claim_allowed":false,"data_classification":"synthetic_educational"}'::JSONB
  )
ON CONFLICT (instrument_id, instrument_version) DO NOTHING;

INSERT INTO audit.model_run (
  model_run_id, session_id, agent_role, provider, model,
  prompt_bundle_id, prompt_bundle_version, prompt_bundle_hash,
  structured_schema_version, input_evidence_hash, status
) VALUES (
  '54000000-0000-0000-0000-000000000001',
  '52000000-0000-0000-0000-000000000001',
  'evaluator', 'smoke', 'g5-deterministic', 'g5-smoke', '1.0.0',
  repeat('a', 64), 'vignette.calibration-transfer.v1', repeat('b', 64), 'ready'
);

SET LOCAL ROLE :"app_role";
SELECT set_config('app.ai_context', '', true);
SELECT set_config('app.current_ai_view', '', true);
SELECT set_config('app.current_role', 'learner', true);
SELECT set_config('app.current_uid', '51000000-0000-0000-0000-000000000001', true);
SELECT set_config('app.current_cohort', 'g5-smoke', true);

INSERT INTO app.calibration_prediction_history (
  history_id, session_id, learner_id, competency_id,
  practice_block_id, scenario_variant_id, phrase_family_id, created_by_role
) VALUES (
  '55000000-0000-0000-0000-000000000001',
  '52000000-0000-0000-0000-000000000001',
  '51000000-0000-0000-0000-000000000001',
  'competency.empathic-check', 'oas-g5-block-smoke',
  'variant-smoke-familiar', 'phrase-smoke-familiar', 'learner'
);

INSERT INTO app.calibration_prediction_revision (
  prediction_revision_id, submission_id, content_hash, history_id,
  session_id, learner_id, revision_no, predicted_success_probability,
  confidence, recorded_sequence, revision_reason, instrument_id,
  instrument_version, evidence_turn_ids, created_by_role
) VALUES (
  '56000000-0000-0000-0000-000000000001',
  '56100000-0000-0000-0000-000000000001', repeat('1', 64),
  '55000000-0000-0000-0000-000000000001',
  '52000000-0000-0000-0000-000000000001',
  '51000000-0000-0000-0000-000000000001',
  1, 0.70, 0.60, 1, '첫 자기예측을 기록했다.',
  'vignette-g5-calibration', '1.0.0',
  ARRAY['53000000-0000-0000-0000-000000000001']::UUID[], 'learner'
);
INSERT INTO app.calibration_prediction_revision (
  prediction_revision_id, submission_id, content_hash, history_id,
  session_id, learner_id, revision_no, supersedes_prediction_revision_id,
  predicted_success_probability, confidence, recorded_sequence,
  revision_reason, instrument_id, instrument_version, evidence_turn_ids,
  created_by_role
) VALUES (
  '56000000-0000-0000-0000-000000000002',
  '56100000-0000-0000-0000-000000000002', repeat('2', 64),
  '55000000-0000-0000-0000-000000000001',
  '52000000-0000-0000-0000-000000000001',
  '51000000-0000-0000-0000-000000000001',
  2, '56000000-0000-0000-0000-000000000001',
  0.55, 0.70, 2, '반대 근거를 보고 공개 전에 예측을 낮췄다.',
  'vignette-g5-calibration', '1.0.0',
  ARRAY['53000000-0000-0000-0000-000000000001']::UUID[], 'learner'
);
INSERT INTO app.calibration_prediction_lock (
  lock_id, submission_id, content_hash, history_id,
  prediction_revision_id, session_id, learner_id,
  locked_sequence, created_by_role
) VALUES (
  '57000000-0000-0000-0000-000000000001',
  '57100000-0000-0000-0000-000000000001', repeat('3', 64),
  '55000000-0000-0000-0000-000000000001',
  '56000000-0000-0000-0000-000000000002',
  '52000000-0000-0000-0000-000000000001',
  '51000000-0000-0000-0000-000000000001', 2, 'learner'
);

DO $$ BEGIN
  BEGIN
    INSERT INTO app.calibration_prediction_revision (
      prediction_revision_id, submission_id, content_hash, history_id,
      session_id, learner_id, revision_no, supersedes_prediction_revision_id,
      predicted_success_probability, confidence, recorded_sequence,
      revision_reason, instrument_id, instrument_version, created_by_role
    ) VALUES (
      '56000000-0000-0000-0000-000000000003',
      '56100000-0000-0000-0000-000000000003', repeat('4', 64),
      '55000000-0000-0000-0000-000000000001',
      '52000000-0000-0000-0000-000000000001',
      '51000000-0000-0000-0000-000000000001',
      3, '56000000-0000-0000-0000-000000000002',
      0.90, 0.90, 3, '공개 후 오염 시도',
      'vignette-g5-calibration', '1.0.0', 'learner'
    );
    RAISE EXCEPTION 'post-lock prediction revision was accepted';
  EXCEPTION WHEN object_not_in_prerequisite_state THEN NULL;
  END;
END $$;

SELECT set_config('app.ai_context', '1', true);
SELECT set_config('app.current_ai_view', 'evaluator', true);
SELECT set_config('app.current_role', 'admin', true);

INSERT INTO app.calibration_performance_observation (
  observation_id, submission_id, content_hash, history_id,
  prediction_lock_id, session_id, learner_id, competency_id,
  practice_block_id, scenario_variant_id, phrase_family_id,
  status, source_kind, perspective, model_run_id,
  instrument_id, instrument_version, uncertainty,
  evidence_turn_ids, counterevidence, revealed_sequence
) VALUES (
  '58000000-0000-0000-0000-000000000001',
  '58100000-0000-0000-0000-000000000001', repeat('5', 64),
  '55000000-0000-0000-0000-000000000001',
  '57000000-0000-0000-0000-000000000001',
  '52000000-0000-0000-0000-000000000001',
  '51000000-0000-0000-0000-000000000001',
  'competency.empathic-check', 'oas-g5-block-smoke',
  'variant-smoke-familiar', 'phrase-smoke-familiar',
  'passed', 'model_inferred', 'independent_observer',
  '54000000-0000-0000-0000-000000000001',
  'vignette-g5-calibration', '1.0.0', 0.20,
  ARRAY['53000000-0000-0000-0000-000000000002']::UUID[],
  ARRAY[]::TEXT[], 3
);

INSERT INTO app.calibration_assessment_snapshot (
  assessment_snapshot_id, submission_id, content_hash, session_id,
  learner_id, competency_id, snapshot_no, source_observation_ids,
  assessment_payload, model_run_id, instrument_id, instrument_version,
  evidence_turn_ids
) VALUES (
  '59000000-0000-0000-0000-000000000001',
  '59100000-0000-0000-0000-000000000001', repeat('6', 64),
  '52000000-0000-0000-0000-000000000001',
  '51000000-0000-0000-0000-000000000001',
  'competency.empathic-check', 1,
  ARRAY['58000000-0000-0000-0000-000000000001']::UUID[],
  '{"competency_id":"competency.empathic-check","pair_count":1,"bias":"insufficient_evidence","improvement":"insufficient_evidence","pairs":[],"excluded_block_ids":[],"counterevidence":["below-minimum"]}'::JSONB,
  '54000000-0000-0000-0000-000000000001',
  'vignette-g5-calibration', '1.0.0',
  ARRAY['53000000-0000-0000-0000-000000000002']::UUID[]
);
INSERT INTO app.calibration_metacognitive_prescription (
  prescription_id, assessment_snapshot_id, session_id, learner_id,
  competency_id, prescription_payload, model_run_id,
  instrument_id, instrument_version, evidence_turn_ids
) VALUES (
  '5a000000-0000-0000-0000-000000000001',
  '59000000-0000-0000-0000-000000000001',
  '52000000-0000-0000-0000-000000000001',
  '51000000-0000-0000-0000-000000000001',
  'competency.empathic-check',
  '{"competency_id":"competency.empathic-check","bias":"insufficient_evidence","practice_mode":"collect_more_evidence","instruction_ko":"같은 역량의 새 장면을 세 번 수행하고 외부평가 전에 예측을 잠근다.","completion_evidence":["three_locked_predictions"]}'::JSONB,
  '54000000-0000-0000-0000-000000000001',
  'vignette-g5-calibration', '1.0.0',
  ARRAY['53000000-0000-0000-0000-000000000002']::UUID[]
);

INSERT INTO app.calibration_transfer_suite (
  transfer_suite_record_id, submission_id, content_hash, suite_key,
  session_id, learner_id, training_phrase_family_ids,
  model_run_id, instrument_id, instrument_version
) VALUES (
  '5b000000-0000-0000-0000-000000000001',
  '5b100000-0000-0000-0000-000000000001', repeat('7', 64),
  'oas-g5-suite-smoke', '52000000-0000-0000-0000-000000000001',
  '51000000-0000-0000-0000-000000000001',
  ARRAY['phrase-smoke-familiar'],
  '54000000-0000-0000-0000-000000000001',
  'vignette-g5-transfer', '1.0.0'
);
INSERT INTO app.calibration_transfer_trial (
  transfer_trial_record_id, transfer_suite_record_id, session_id,
  learner_id, trial_key, competency_id, scenario_variant_id,
  context_variant, relationship_style, difficulty_level,
  expression_variant, synthetic_subgroup, scenario_family_id,
  phrase_family_id, status, uncertainty, evidence_turn_ids,
  counterevidence, model_run_id, instrument_id, instrument_version
) VALUES
  (
    '5c000000-0000-0000-0000-000000000001',
    '5b000000-0000-0000-0000-000000000001',
    '52000000-0000-0000-0000-000000000001',
    '51000000-0000-0000-0000-000000000001',
    'oas-g5-transfer-smoke-a', 'competency.empathic-check',
    'variant-smoke-unseen-a', 'school', 'withdrawn', 3,
    'indirect', 'synthetic-a', 'family-unseen-a', 'phrase-adapted-a',
    'passed', 0.20,
    ARRAY['53000000-0000-0000-0000-000000000001']::UUID[], ARRAY[]::TEXT[],
    '54000000-0000-0000-0000-000000000001',
    'vignette-g5-transfer', '1.0.0'
  ),
  (
    '5c000000-0000-0000-0000-000000000002',
    '5b000000-0000-0000-0000-000000000001',
    '52000000-0000-0000-0000-000000000001',
    '51000000-0000-0000-0000-000000000001',
    'oas-g5-transfer-smoke-b', 'competency.empathic-check',
    'variant-smoke-unseen-b', 'home', 'ambivalent', 4,
    'metaphoric', 'synthetic-b', 'family-unseen-b', 'phrase-adapted-b',
    'failed', 0.30,
    ARRAY['53000000-0000-0000-0000-000000000002']::UUID[],
    ARRAY['client_response_not_engaged'],
    '54000000-0000-0000-0000-000000000001',
    'vignette-g5-transfer', '1.0.0'
  );
INSERT INTO app.calibration_transfer_assessment (
  transfer_assessment_id, transfer_suite_record_id, session_id,
  learner_id, competency_id, source_trial_ids, assessment_payload,
  evidence_turn_ids, model_run_id, instrument_id, instrument_version
) VALUES (
  '5d000000-0000-0000-0000-000000000001',
  '5b000000-0000-0000-0000-000000000001',
  '52000000-0000-0000-0000-000000000001',
  '51000000-0000-0000-0000-000000000001',
  'competency.empathic-check',
  ARRAY['5c000000-0000-0000-0000-000000000001','5c000000-0000-0000-0000-000000000002']::UUID[],
  '{"competency_id":"competency.empathic-check","trial_count":2,"observed_trial_count":2,"success_rate":0.5,"coverage":{"contexts":2},"eligible":false,"transfer_verified":false,"blockers":["below-minimum"],"evidence_refs":[],"counterevidence":["client_response_not_engaged"]}'::JSONB,
  ARRAY['53000000-0000-0000-0000-000000000001','53000000-0000-0000-0000-000000000002']::UUID[],
  '54000000-0000-0000-0000-000000000001',
  'vignette-g5-transfer', '1.0.0'
);
INSERT INTO app.calibration_subgroup_drift_report (
  drift_report_id, transfer_suite_record_id, session_id, learner_id,
  competency_id, source_trial_ids, report_payload, model_run_id,
  instrument_id, instrument_version
) VALUES (
  '5e000000-0000-0000-0000-000000000001',
  '5b000000-0000-0000-0000-000000000001',
  '52000000-0000-0000-0000-000000000001',
  '51000000-0000-0000-0000-000000000001',
  'competency.empathic-check',
  ARRAY['5c000000-0000-0000-0000-000000000001','5c000000-0000-0000-0000-000000000002']::UUID[],
  '{"competency_id":"competency.empathic-check","status":"insufficient_evidence","compared_subgroups":[],"subgroup_results":[],"threshold":0.2,"notice_ko":"교육용 합성 subgroup 관측이 부족해 드리프트를 판정하지 않는다."}'::JSONB,
  '54000000-0000-0000-0000-000000000001',
  'vignette-g5-transfer', '1.0.0'
);

-- Learner-self, unrelated learner, teacher cohort and cross-cohort isolation.
SELECT set_config('app.ai_context', '', true);
SELECT set_config('app.current_ai_view', '', true);
SELECT set_config('app.current_role', 'learner', true);
SELECT set_config('app.current_uid', '51000000-0000-0000-0000-000000000001', true);
DO $$ BEGIN
  IF (SELECT count(*) FROM app.calibration_prediction_history) <> 1 THEN
    RAISE EXCEPTION 'learner self G5 RLS smoke failed';
  END IF;
END $$;
SELECT set_config('app.current_uid', '51000000-0000-0000-0000-000000000003', true);
DO $$ BEGIN
  IF (SELECT count(*) FROM app.calibration_prediction_history) <> 0 THEN
    RAISE EXCEPTION 'unrelated learner G5 RLS leaked data';
  END IF;
END $$;
SELECT set_config('app.current_role', 'instructor', true);
SELECT set_config('app.current_uid', '51000000-0000-0000-0000-000000000002', true);
SELECT set_config('app.current_cohort', 'g5-smoke', true);
DO $$ BEGIN
  IF (SELECT count(*) FROM app.calibration_transfer_suite) <> 1 THEN
    RAISE EXCEPTION 'teacher cohort G5 RLS smoke failed';
  END IF;
END $$;
SELECT set_config('app.current_cohort', 'g5-other', true);
DO $$ BEGIN
  IF (SELECT count(*) FROM app.calibration_transfer_suite) <> 0 THEN
    RAISE EXCEPTION 'teacher cross-cohort G5 RLS leaked data';
  END IF;
END $$;

SELECT set_config('app.current_cohort', 'g5-smoke', true);
INSERT INTO app.calibration_teacher_review_event (
  review_id, submission_id, content_hash, target_kind, target_id,
  session_id, learner_id, review_no, disposition, correction_payload,
  review_reason, evidence_turn_ids, counterevidence,
  created_by_uid, created_by_role
) VALUES (
  '5f000000-0000-0000-0000-000000000001',
  '5f100000-0000-0000-0000-000000000001', repeat('8', 64),
  'calibration_assessment', '59000000-0000-0000-0000-000000000001',
  '52000000-0000-0000-0000-000000000001',
  '51000000-0000-0000-0000-000000000001',
  1, 'confirmed', '{}'::JSONB, '역량별 근거와 불확실성을 확인했다.',
  ARRAY['53000000-0000-0000-0000-000000000002']::UUID[], ARRAY[]::TEXT[],
  '51000000-0000-0000-0000-000000000002', 'instructor'
);

DO $$ BEGIN
  BEGIN
    INSERT INTO app.calibration_teacher_review_event (
      review_id, submission_id, content_hash, target_kind, target_id,
      session_id, learner_id, review_no, supersedes_review_id,
      disposition, correction_payload, review_reason,
      created_by_uid, created_by_role
    ) VALUES (
      '5f000000-0000-0000-0000-000000000002',
      '5f100000-0000-0000-0000-000000000002', repeat('9', 64),
      'calibration_assessment', '59000000-0000-0000-0000-000000000001',
      '52000000-0000-0000-0000-000000000001',
      '51000000-0000-0000-0000-000000000001',
      2, '5f000000-0000-0000-0000-000000000001',
      'corrected', '{"raw_transcript":"forbidden"}'::JSONB,
      '금지된 본문 복제 시도',
      '51000000-0000-0000-0000-000000000002', 'instructor'
    );
    RAISE EXCEPTION 'raw transcript payload was accepted';
  EXCEPTION WHEN check_violation THEN NULL;
  END;
  BEGIN
    INSERT INTO app.calibration_teacher_review_event (
      review_id, submission_id, content_hash, target_kind, target_id,
      session_id, learner_id, review_no, supersedes_review_id,
      disposition, correction_payload, review_reason,
      created_by_uid, created_by_role
    ) VALUES (
      '5f000000-0000-0000-0000-000000000003',
      '5f100000-0000-0000-0000-000000000003', repeat('a', 64),
      'calibration_assessment', '59000000-0000-0000-0000-000000000001',
      '52000000-0000-0000-0000-000000000001',
      '51000000-0000-0000-0000-000000000001',
      2, '5f000000-0000-0000-0000-000000000001',
      'corrected', '{"total_score":0.9}'::JSONB,
      '금지된 합산 점수 시도',
      '51000000-0000-0000-0000-000000000002', 'instructor'
    );
    RAISE EXCEPTION 'aggregate score payload was accepted';
  EXCEPTION WHEN check_violation THEN NULL;
  END;
END $$;

RESET ROLE;

DO $$ BEGIN
  BEGIN
    UPDATE app.calibration_prediction_revision
    SET predicted_success_probability = 1.0
    WHERE prediction_revision_id = '56000000-0000-0000-0000-000000000001';
    RAISE EXCEPTION 'append-only calibration revision update was accepted';
  EXCEPTION WHEN object_not_in_prerequisite_state THEN NULL;
  END;
  BEGIN
    INSERT INTO app.calibration_performance_observation (
      observation_id, submission_id, content_hash, history_id,
      prediction_lock_id, session_id, learner_id, competency_id,
      practice_block_id, scenario_variant_id, phrase_family_id,
      status, source_kind, perspective, model_run_id,
      instrument_id, instrument_version, uncertainty,
      evidence_turn_ids, revealed_sequence
    ) VALUES (
      '58000000-0000-0000-0000-000000000009',
      '58100000-0000-0000-0000-000000000001', repeat('f', 64),
      '55000000-0000-0000-0000-000000000001',
      '57000000-0000-0000-0000-000000000001',
      '52000000-0000-0000-0000-000000000001',
      '51000000-0000-0000-0000-000000000001',
      'competency.empathic-check', 'oas-g5-block-smoke',
      'variant-smoke-familiar', 'phrase-smoke-familiar',
      'passed', 'model_inferred', 'independent_observer',
      '54000000-0000-0000-0000-000000000001',
      'vignette-g5-calibration', '1.0.0', 0.2,
      ARRAY['53000000-0000-0000-0000-000000000002']::UUID[], 4
    );
    RAISE EXCEPTION 'changed idempotent observation was accepted';
  EXCEPTION WHEN unique_violation THEN NULL;
  END;
END $$;

ROLLBACK;

SELECT 'g5_calibration_transfer_rollback_residue' AS check_name,
  (
    (SELECT count(*) FROM app.calibration_prediction_history
      WHERE history_id = '55000000-0000-0000-0000-000000000001')
    + (SELECT count(*) FROM app.calibration_performance_observation
      WHERE observation_id = '58000000-0000-0000-0000-000000000001')
    + (SELECT count(*) FROM app.calibration_transfer_suite
      WHERE transfer_suite_record_id = '5b000000-0000-0000-0000-000000000001')
    + (SELECT count(*) FROM app.calibration_teacher_review_event
      WHERE review_id = '5f000000-0000-0000-0000-000000000001')
    + (SELECT count(*) FROM app.app_user
      WHERE user_id = '51000000-0000-0000-0000-000000000001')
  ) AS residue_count;