diff --git a/giant/cli.py b/giant/cli.py
index bdce197..56d9cb6 100644
--- a/giant/cli.py
+++ b/giant/cli.py
@@ -296,7 +296,7 @@ def predict(
                 "pre_x":        chunk["pre_pos"][:, 0],
                 "pre_y":        chunk["pre_pos"][:, 1],
                 "pre_z":        chunk["pre_pos"][:, 2],
-                "pre_energy":   chunk["pre_energy"],
+                "pre_E":   chunk["pre_E"],
                 "pre_dir_x":    chunk["pre_dir"][:, 0],
                 "pre_dir_y":    chunk["pre_dir"][:, 1],
                 "pre_dir_z":    chunk["pre_dir"][:, 2],
diff --git a/giant/data/loader.py b/giant/data/loader.py
index a7be53c..9489aad 100644
--- a/giant/data/loader.py
+++ b/giant/data/loader.py
@@ -21,13 +21,13 @@ def _df_to_dict(df: pd.DataFrame) -> dict[str, np.ndarray]:
         "event_id": df["event_id"].to_numpy(),
         "pdg": df["pdg"].to_numpy(dtype=np.int32),
         "pre_pos": df[["pre_x", "pre_y", "pre_z"]].to_numpy(dtype=np.float32),
-        "pre_energy": df["pre_energy"].to_numpy(dtype=np.float32),
+        "pre_E": df["pre_E"].to_numpy(dtype=np.float32),
         "pre_dir": df[["pre_dir_x", "pre_dir_y", "pre_dir_z"]].to_numpy(dtype=np.float32),
         "material": df["material"].to_numpy(dtype=object),
         "layer_id": df["layer_id"].to_numpy(dtype=np.int32),
         "n_sec": df["child_track_ids"].apply(len).to_numpy(dtype=np.int32),
         "step_length": df["step_length"].to_numpy(dtype=np.float32),
-        "delta_e": (df["pre_energy"] - df["post_energy"]).to_numpy(dtype=np.float32),
+        "delta_e": (df["pre_E"] - df["post_E"]).to_numpy(dtype=np.float32),
         "edep": df["edep"].to_numpy(dtype=np.float32),
         "post_dir": df[["post_dir_x", "post_dir_y", "post_dir_z"]].to_numpy(dtype=np.float32),
     }
@@ -51,7 +51,7 @@ def iter_file_chunks(path: str | Path) -> Iterator[dict[str, np.ndarray]]:
 
 _COND_COLS = [
     "event_id", "pdg",
-    "pre_x", "pre_y", "pre_z", "pre_energy",
+    "pre_x", "pre_y", "pre_z", "pre_E",
     "pre_dir_x", "pre_dir_y", "pre_dir_z",
     "material", "layer_id", "child_track_ids",
 ]
@@ -62,7 +62,7 @@ def _cond_df_to_dict(df: pd.DataFrame) -> dict[str, np.ndarray]:
         "event_id": df["event_id"].to_numpy(),
         "pdg": df["pdg"].to_numpy(dtype=np.int32),
         "pre_pos": df[["pre_x", "pre_y", "pre_z"]].to_numpy(dtype=np.float32),
-        "pre_energy": df["pre_energy"].to_numpy(dtype=np.float32),
+        "pre_E": df["pre_E"].to_numpy(dtype=np.float32),
         "pre_dir": df[["pre_dir_x", "pre_dir_y", "pre_dir_z"]].to_numpy(dtype=np.float32),
         "material": df["material"].to_numpy(dtype=object),
         "layer_id": df["layer_id"].to_numpy(dtype=np.int32),
diff --git a/giant/data/transforms.py b/giant/data/transforms.py
index 00fe25b..a05c983 100644
--- a/giant/data/transforms.py
+++ b/giant/data/transforms.py
@@ -129,7 +129,7 @@ def build_cond_features(
     """Build conditioning arrays only — no target, no post-step variables."""
     cond_cont = np.column_stack([
         data["pre_pos"],
-        log_transform(data["pre_energy"]),
+        log_transform(data["pre_E"]),
         data["pre_dir"],
         data["layer_id"].astype(np.float32),
         data["n_sec"].astype(np.float32),
@@ -168,7 +168,7 @@ def build_features(
 
     cond_cont = np.column_stack([
         data["pre_pos"],
-        log_transform(data["pre_energy"]),
+        log_transform(data["pre_E"]),
         data["pre_dir"],
         data["layer_id"].astype(np.float32),
         data["n_sec"].astype(np.float32),