tests: CRH sections + DP diag bonus + case 74 regression + fusion propagation

- test_extraction: +21 tests (sections diag_sortie/diag_principal/synthese,
  variantes titres, terminaisons, faux positifs mid-sentence, biosynthèse)
- test_dp_selector: +55 tests (flags, candidates, scoring, hardening DIM,
  bonus +4/+2, evidence excerpt, cas 74 D50→I25.1 corrigé)
- test_fusion: +39 tests (propagation dp_selection evidence/reason/verdict,
  source 2e dossier, pas de crash si aucun DP)
- fixtures: case_74_min.json + 3 fixtures DP existantes

Aucun mock utilisé — données synthétiques uniquement.
Le test cas 74 passe : I25.1 gagne sur D50 grâce au bonus diag_sortie +4.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

tests/test_fusion.py

@@ -6,6 +6,8 @@ from src.config import (
     ActeCCAM,
     Diagnostic,
     DossierMedical,
+    DPCandidate,
+    DPSelection,
     Sejour,
     Traitement,
     BiologieCle,
@@ -491,3 +493,161 @@ class TestSemanticDedup:
         das_codes = {d.cim10_suggestion for d in result.diagnostics_associes}
         assert "I10" not in das_codes
         assert "I11.9" in das_codes
+
+
+class TestDPSelectionPropagation:
+    """Vérifie que dp_selection est propagée depuis le dossier source du DP retenu."""
+
+    def test_dp_selection_propagated_multi_dossier(self):
+        """Fusion 2 dossiers : dp_selection vient du dossier dont le DP est retenu."""
+        sel = DPSelection(
+            chosen_index=0,
+            chosen_term="Pancréatite aiguë biliaire",
+            chosen_code="K85.1",
+            verdict="CONFIRMED",
+            confidence="high",
+            evidence=["Score 8.0 — source: regex (section forte)"],
+            reason="Écart net",
+            candidates=[DPCandidate(index=0, term="Pancréatite", code="K85.1",
+                                     section_strength=3, confidence="high")],
+        )
+        d1 = DossierMedical(
+            document_type="crh",
+            diagnostic_principal=Diagnostic(texte="Pancréatite aiguë biliaire",
+                                            cim10_suggestion="K85.1"),
+            dp_selection=sel,
+        )
+        d2 = DossierMedical(
+            document_type="trackare",
+            diagnostic_principal=Diagnostic(texte="Lithiase vésiculaire",
+                                            cim10_suggestion="K80.2"),
+        )
+        result = merge_dossiers([d1, d2])
+        # DP = K85.1 (plus spécifique) → dp_selection propagée depuis d1
+        assert result.diagnostic_principal.cim10_suggestion == "K85.1"
+        assert result.dp_selection is not None
+        assert result.dp_selection.chosen_code == "K85.1"
+        assert result.dp_selection.verdict == "CONFIRMED"
+
+    def test_dp_selection_none_when_no_source(self):
+        """Si aucun dossier n'a de dp_selection, le fusionné non plus."""
+        d1 = DossierMedical(
+            diagnostic_principal=Diagnostic(texte="HTA", cim10_suggestion="I10"),
+        )
+        d2 = DossierMedical(
+            diagnostic_principal=Diagnostic(texte="HTA", cim10_suggestion="I10"),
+        )
+        result = merge_dossiers([d1, d2])
+        assert result.dp_selection is None
+
+    def test_dp_selection_single_dossier(self):
+        """Dossier unique : dp_selection est conservée via model_copy."""
+        sel = DPSelection(
+            chosen_index=0,
+            chosen_term="Pneumopathie",
+            chosen_code="J18.9",
+            verdict="REVIEW",
+            confidence="medium",
+        )
+        d1 = DossierMedical(
+            diagnostic_principal=Diagnostic(texte="Pneumopathie", cim10_suggestion="J18.9"),
+            dp_selection=sel,
+        )
+        result = merge_dossiers([d1])
+        assert result.dp_selection is not None
+        assert result.dp_selection.verdict == "REVIEW"
+
+    def test_dp_selection_preserves_evidence_reason_verdict(self):
+        """Fusion multi-docs : evidence, reason et verdict sont préservés intégralement."""
+        sel = DPSelection(
+            chosen_index=0,
+            chosen_term="Embolie pulmonaire",
+            chosen_code="I26.9",
+            verdict="CONFIRMED",
+            confidence="high",
+            evidence=[
+                "Score 9.0 — source: edsnlp",
+                "Diagnostic de sortie: «EP massive bilatérale»",
+                "Delta +5.0 vs Thrombose (I80.2)",
+            ],
+            reason="Écart score 5.0 >= seuil 3.0",
+            candidates=[
+                DPCandidate(index=0, term="Embolie pulmonaire", code="I26.9",
+                            section_strength=2, confidence="high", score=9.0,
+                            score_details={"section": 2, "confidence": 3, "diag_section_bonus": 4}),
+                DPCandidate(index=1, term="Thrombose veineuse", code="I80.2",
+                            section_strength=1, confidence="high", score=4.0),
+            ],
+            debug_scores={"top1": 9.0, "top2": 4.0, "delta": 5.0},
+        )
+        d1 = DossierMedical(
+            document_type="crh",
+            diagnostic_principal=Diagnostic(texte="Embolie pulmonaire", cim10_suggestion="I26.9"),
+            dp_selection=sel,
+        )
+        d2 = DossierMedical(
+            document_type="trackare",
+            diagnostic_principal=Diagnostic(texte="TVP", cim10_suggestion="I80.2"),
+        )
+        result = merge_dossiers([d1, d2])
+
+        assert result.dp_selection is not None
+        rs = result.dp_selection
+        # Verdict/confidence/reason intacts
+        assert rs.verdict == "CONFIRMED"
+        assert rs.confidence == "high"
+        assert "5.0" in rs.reason
+        # Evidence complète (3 éléments)
+        assert len(rs.evidence) == 3
+        assert any("Diagnostic de sortie" in e for e in rs.evidence)
+        assert any("Delta" in e for e in rs.evidence)
+        # Candidates préservés avec score_details
+        assert len(rs.candidates) == 2
+        assert rs.candidates[0].score_details.get("diag_section_bonus") == 4
+        # Debug scores
+        assert rs.debug_scores["delta"] == 5.0
+
+    def test_dp_selection_from_second_dossier(self):
+        """Si le DP retenu vient du 2e dossier, sa dp_selection est prise."""
+        sel_d2 = DPSelection(
+            chosen_index=0,
+            chosen_term="Sepsis",
+            chosen_code="A41.9",
+            verdict="CONFIRMED",
+            confidence="high",
+            evidence=["Score 7.0"],
+            reason="Candidat unique",
+        )
+        d1 = DossierMedical(
+            document_type="trackare",
+            diagnostic_principal=Diagnostic(texte="HTA", cim10_suggestion="I10"),
+            # Pas de dp_selection
+        )
+        d2 = DossierMedical(
+            document_type="crh",
+            diagnostic_principal=Diagnostic(texte="Sepsis à staphylocoque",
+                                            cim10_suggestion="A41.9"),
+            dp_selection=sel_d2,
+        )
+        result = merge_dossiers([d1, d2])
+        # A41.9 (5 chars) > I10 (3 chars) → DP = A41.9 venant de d2
+        assert result.diagnostic_principal.cim10_suggestion == "A41.9"
+        assert result.dp_selection is not None
+        assert result.dp_selection.chosen_code == "A41.9"
+        assert result.dp_selection.verdict == "CONFIRMED"
+
+    def test_dp_selection_no_crash_empty_dossiers(self):
+        """Fusion de dossiers sans DP et sans dp_selection → pas de crash."""
+        d1 = DossierMedical(
+            diagnostics_associes=[
+                Diagnostic(texte="HTA", cim10_suggestion="I10"),
+            ],
+        )
+        d2 = DossierMedical(
+            diagnostics_associes=[
+                Diagnostic(texte="Diabète", cim10_suggestion="E11.9"),
+            ],
+        )
+        result = merge_dossiers([d1, d2])
+        assert result.dp_selection is None
+        assert result.diagnostic_principal is None