diff --git a/tests/domain/epc_prediction/test_component_accuracy_gate.py b/tests/domain/epc_prediction/test_component_accuracy_gate.py
index 2b0ee9fb..cc262c17 100644
--- a/tests/domain/epc_prediction/test_component_accuracy_gate.py
+++ b/tests/domain/epc_prediction/test_component_accuracy_gate.py
@@ -41,27 +41,42 @@ _FIXTURE = Path(__file__).parents[3] / "tests" / "fixtures" / "epc_prediction"
 # mode tipped, and it tipped entirely inside one near-tie pre-1900↔1900-29 (A↔B)
 # cohort. wall_insulation_type / floor_construction / has_hot_water_cylinder / has_pv
 # moved 3-6pp the same way. The tighten-only ratchet resumes from these new values.
+#
+# Re-baselined again under ADR-0037 (full-SAP mapper completion): full-SAP
+# (on-construction) certs previously mapped property_type=None, so the hard cohort
+# filter (comparable_properties.py — `c.epc.property_type == target.property_type`)
+# silently excluded them from EVERY cohort, as donors and as targets. Mapping
+# property_type correctly admits these real lodged EPCs as comparables — another
+# ground-truth-method change. Net effect over the n=36 fixture: **16 components
+# better, 4 worse, 6 unchanged**. The gains are concentrated in the physical /
+# geometric characteristics full-SAP certs measure accurately — window_count
+# residual 3.83->1.69, total_window_area 3.82->3.72, building_parts 0.33->0.12,
+# floor_construction 0.78->0.91, construction_age_band 0.50->0.78, modal_glazing
+# 0.56->0.84, walls/room-in-roof/heating-control all up. The 4 that fell are the
+# new-build-vs-old-stock service mismatch on 1-2 targets each (heating_main_fuel
+# 0.9722->0.9394, water_heating_fuel ->0.9495, cylinder_insulation_type 0.6667->
+# 0.3333) plus floor_area (+0.31 MAE). Tighten-only resumes from these values.
 _RATE_FLOORS: dict[str, float] = {
-    "wall_construction": 0.8889,
-    "wall_insulation_type": 0.7778,
-    "construction_age_band": 0.5000,
-    "construction_age_band_pm1": 0.8333,
+    "wall_construction": 0.9091,
+    "wall_insulation_type": 0.8687,
+    "construction_age_band": 0.7778,
+    "construction_age_band_pm1": 0.9091,
     "roof_construction": 0.7222,
-    "floor_construction": 0.7812,
-    "heating_main_fuel": 0.9722,
-    "heating_main_category": 0.9444,
-    "heating_main_control": 0.8056,
-    "water_heating_fuel": 0.9722,
-    "water_heating_code": 0.9444,
-    "has_hot_water_cylinder": 0.8333,
-    "cylinder_insulation_type": 0.5000,
+    "floor_construction": 0.9053,
+    "heating_main_fuel": 0.9394,
+    "heating_main_category": 0.9596,
+    "heating_main_control": 0.9091,
+    "water_heating_fuel": 0.9495,
+    "water_heating_code": 0.9798,
+    "has_hot_water_cylinder": 0.8687,
+    "cylinder_insulation_type": 0.3333,
     "secondary_heating_type": 0.0000,
     "roof_insulation_thickness": 0.4118,
     "roof_insulation_thickness_pm1": 0.4118,
     "floor_insulation": 0.9375,
-    "has_room_in_roof": 0.8333,
-    "modal_glazing_type": 0.5556,
-    "has_pv": 0.9444,
+    "has_room_in_roof": 0.9495,
+    "modal_glazing_type": 0.8384,
+    "has_pv": 0.9798,
     "solar_water_heating": 1.0000,
 }
 
@@ -77,11 +92,16 @@ _RATE_FLOORS: dict[str, float] = {
 # the other way as small-sample noise (one target's shift moves an n=36 MAE more
 # than that). The ceiling still pins the new deterministic value exactly, so the
 # tighten-only ratchet resumes from here.
+# total_window_area / building_parts / door_count all tightened under ADR-0037
+# (full-SAP certs admitted as donors — their measured geometry sharpens the
+# dimensional predictions); floor_area loosened 12.0378 -> 12.0586 as the one
+# physical residual that fell (1-2 targets picking a new-build donor). See the
+# _RATE_FLOORS note above.
 _RESIDUAL_CEILINGS: dict[str, float] = {
-    "floor_area": 12.0378,
-    "total_window_area": 4.4067,
-    "building_parts": 0.3333,
-    "door_count": 0.6389,
+    "floor_area": 12.0586,
+    "total_window_area": 3.7184,
+    "building_parts": 0.1212,
+    "door_count": 0.3131,
 }
 
 _TOLERANCE = 1e-3