diff --git a/app/services/recipe/element_classifier.py b/app/services/recipe/element_classifier.py
index ace1f74..991aa00 100644
--- a/app/services/recipe/element_classifier.py
+++ b/app/services/recipe/element_classifier.py
@@ -40,6 +40,17 @@ _HEURISTIC: list[tuple[list[str], str]] = [
 ]
 
 
+def _safe_json_list(val) -> list:
+    if isinstance(val, list):
+        return val
+    if isinstance(val, str):
+        try:
+            return json.loads(val)
+        except Exception:
+            return []
+    return []
+
+
 @dataclass(frozen=True)
 class IngredientProfile:
     name: str
@@ -71,6 +82,8 @@ class ElementClassifier:
     def classify(self, ingredient_name: str) -> IngredientProfile:
         """Return element profile for a single ingredient name."""
         name = ingredient_name.lower().strip()
+        if not name:
+            return IngredientProfile(name="", elements=[], source="heuristic")
         row = self._store._fetch_one(
             "SELECT * FROM ingredient_profiles WHERE name = ?", (name,)
         )
@@ -91,7 +104,7 @@ class ElementClassifier:
     def _row_to_profile(self, row: dict) -> IngredientProfile:
         return IngredientProfile(
             name=row["name"],
-            elements=json.loads(row.get("elements") or "[]"),
+            elements=_safe_json_list(row.get("elements")),
             fat_pct=row.get("fat_pct") or 0.0,
             fat_saturated_pct=row.get("fat_saturated_pct") or 0.0,
             moisture_pct=row.get("moisture_pct") or 0.0,
@@ -100,7 +113,7 @@ class ElementClassifier:
             binding_score=row.get("binding_score") or 0,
             glutamate_mg=row.get("glutamate_mg") or 0.0,
             ph_estimate=row.get("ph_estimate"),
-            flavor_molecule_ids=json.loads(row.get("flavor_molecule_ids") or "[]"),
+            flavor_molecule_ids=_safe_json_list(row.get("flavor_molecule_ids")),
             heat_stable=bool(row.get("heat_stable", 1)),
             add_timing=row.get("add_timing") or "any",
             acid_type=row.get("acid_type"),
@@ -113,8 +126,10 @@ class ElementClassifier:
         )
 
     def _heuristic_profile(self, name: str) -> IngredientProfile:
-        elements = []
+        seen: set[str] = set()
+        elements: list[str] = []
         for keywords, element in _HEURISTIC:
-            if any(kw in name for kw in keywords):
+            if element not in seen and any(kw in name for kw in keywords):
                 elements.append(element)
+                seen.add(element)
         return IngredientProfile(name=name, elements=elements, source="heuristic")
diff --git a/tests/services/recipe/test_element_classifier.py b/tests/services/recipe/test_element_classifier.py
index 679aecb..5fb37c1 100644
--- a/tests/services/recipe/test_element_classifier.py
+++ b/tests/services/recipe/test_element_classifier.py
@@ -35,6 +35,7 @@ def test_classify_known_ingredient(store_with_profiles):
     assert "Richness" in profile.elements
     assert profile.fat_pct == pytest.approx(81.0)
     assert profile.name == "butter"
+    assert profile.source == "db"
 
 
 def test_classify_unknown_ingredient_uses_heuristic(store_with_profiles):
@@ -42,7 +43,7 @@ def test_classify_unknown_ingredient_uses_heuristic(store_with_profiles):
     clf = ElementClassifier(store_with_profiles)
     profile = clf.classify("ghost pepper hot sauce")
     # Heuristic should detect acid / aroma
-    assert len(profile.elements) > 0
+    assert "Aroma" in profile.elements  # "pepper" in name matches Aroma heuristic
     assert profile.name == "ghost pepper hot sauce"