diff --git a/user_tools/src/spark_rapids_pytools/resources/qualx/models/xgboost/combined.json b/user_tools/src/spark_rapids_pytools/resources/qualx/models/xgboost/combined.json
index 664ebea94..6b009e193 100644
--- a/user_tools/src/spark_rapids_pytools/resources/qualx/models/xgboost/combined.json
+++ b/user_tools/src/spark_rapids_pytools/resources/qualx/models/xgboost/combined.json
@@ -1 +1 @@
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diff --git a/user_tools/src/spark_rapids_pytools/resources/qualx/models/xgboost/databricks-aws.json b/user_tools/src/spark_rapids_pytools/resources/qualx/models/xgboost/databricks-aws.json
index 4183ac665..9f3b10fe2 100644
--- a/user_tools/src/spark_rapids_pytools/resources/qualx/models/xgboost/databricks-aws.json
+++ b/user_tools/src/spark_rapids_pytools/resources/qualx/models/xgboost/databricks-aws.json
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diff --git a/user_tools/src/spark_rapids_pytools/resources/qualx/models/xgboost/databricks-azure.json b/user_tools/src/spark_rapids_pytools/resources/qualx/models/xgboost/databricks-azure.json
index 094eb9ce4..e0a2c75b9 100644
--- a/user_tools/src/spark_rapids_pytools/resources/qualx/models/xgboost/databricks-azure.json
+++ b/user_tools/src/spark_rapids_pytools/resources/qualx/models/xgboost/databricks-azure.json
@@ -1 +1 @@
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diff --git a/user_tools/src/spark_rapids_pytools/resources/qualx/models/xgboost/dataproc.json b/user_tools/src/spark_rapids_pytools/resources/qualx/models/xgboost/dataproc.json
index 3cd52ae1c..0fd6a4367 100644
--- a/user_tools/src/spark_rapids_pytools/resources/qualx/models/xgboost/dataproc.json
+++ b/user_tools/src/spark_rapids_pytools/resources/qualx/models/xgboost/dataproc.json
@@ -1 +1 @@
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\ No newline at end of file
diff --git a/user_tools/src/spark_rapids_tools/tools/qualx/model.py b/user_tools/src/spark_rapids_tools/tools/qualx/model.py
index 6415644ab..b6f14382e 100644
--- a/user_tools/src/spark_rapids_tools/tools/qualx/model.py
+++ b/user_tools/src/spark_rapids_tools/tools/qualx/model.py
@@ -49,6 +49,7 @@
         'scaleFactor',
         'sparkVersion',
         'sqlID',
+        'xgpu_appDuration',
     ]
 )
 
@@ -164,6 +165,8 @@ def predict(
     ]
     if 'split' in cpu_aug_tbl:
         select_columns.append('split')
+    if 'xgpu_appDuration' in cpu_aug_tbl:
+        select_columns.append('xgpu_appDuration')
 
     # join predictions with select input features
     results_df = (
@@ -230,9 +233,18 @@ def extract_model_features(
             )
         # train/validation dataset with CPU + GPU runs
         gpu_aug_tbl = gpu_aug_tbl[
-            ['appName', 'scaleFactor', 'sqlID', 'Duration', 'description']
+            [
+                'appName',
+                'scaleFactor',
+                'sqlID',
+                'Duration',
+                'description',
+                'appDuration',
+            ]
         ]
-        gpu_aug_tbl = gpu_aug_tbl.rename(columns={'Duration': 'xgpu_Duration'})
+        gpu_aug_tbl = gpu_aug_tbl.rename(
+            columns={'Duration': 'xgpu_Duration', 'appDuration': 'xgpu_appDuration'}
+        )
         cpu_aug_tbl = cpu_aug_tbl.merge(
             gpu_aug_tbl,
             on=['appName', 'scaleFactor', 'sqlID', 'description'],
diff --git a/user_tools/src/spark_rapids_tools/tools/qualx/preprocess.py b/user_tools/src/spark_rapids_tools/tools/qualx/preprocess.py
index 1408ede7a..9396df9e5 100644
--- a/user_tools/src/spark_rapids_tools/tools/qualx/preprocess.py
+++ b/user_tools/src/spark_rapids_tools/tools/qualx/preprocess.py
@@ -330,7 +330,9 @@ def infer_app_meta(eventlogs: List[str]) -> Mapping[str, Mapping]:
                         )
                     toc_list.append(tmp)
 
-        if toc_list:
+        if not toc_list:
+            raise ValueError(f'No CSV files found for: {ds_name}')
+        else:
             toc = pd.concat(toc_list)
             raw_features = extract_raw_features(toc, node_level_supp, qualtool_filter)
             if raw_features.empty:
@@ -415,7 +417,7 @@ def combine_tables(table_name: str) -> pd.DataFrame:
 
     # normalize WholeStageCodegen labels
     ops_tbl.loc[
-        ops_tbl['nodeName'].str.startswith('WholeStageCodegen') == True, 'nodeName'
+        ops_tbl['nodeName'].str.startswith('WholeStageCodegen'), 'nodeName'
     ] = 'WholeStageCodegen'
 
     # format WholeStageCodegen for merging
@@ -449,7 +451,7 @@ def combine_tables(table_name: str) -> pd.DataFrame:
     ]
     for op in dynamic_op_labels:
         sql_ops_counter.loc[
-            sql_ops_counter['nodeName'].str.startswith(op) == True, 'nodeName'
+            sql_ops_counter['nodeName'].str.startswith(op), 'nodeName'
         ] = op
 
     # count occurrences
@@ -533,7 +535,7 @@ def combine_tables(table_name: str) -> pd.DataFrame:
 
     # filter rows w/ sqlID
     sql_job_agg_tbl['hasSqlID'] = sql_job_agg_tbl['sqlID'] >= 0
-    full_tbl = sql_job_agg_tbl[sql_job_agg_tbl['hasSqlID'] == True]
+    full_tbl = sql_job_agg_tbl[sql_job_agg_tbl['hasSqlID']]
 
     # add runType features from toc
     app_runtype = toc[['appId', 'runType']].drop_duplicates()
@@ -929,21 +931,22 @@ def scan_tbl(
                 sql_to_stage, left_on='ID', right_on='stageId'
             )
             total_stage_time = (
-                stage_agg_tbl[['sqlID', 'ID', 'Duration']]
+                stage_agg_tbl[['sqlID', 'Duration']]
                 .groupby('sqlID')
                 .agg('sum')
                 .reset_index()
             )
             failed_stage_time = (
                 stage_agg_tbl[['sqlID', 'ID', 'Duration']]
-                .merge(failed_stages, left_on='ID', right_on='stageId', how='inner')
+                .merge(failed_stages, left_on='ID', right_on='stageId', how='inner')[
+                    ['sqlID', 'Duration']
+                ]
                 .groupby('sqlID')
                 .agg('sum')
                 .reset_index()
-                .drop(columns=['sqlID'])
             )
             stage_times = total_stage_time.merge(
-                failed_stage_time, on='ID', how='inner'
+                failed_stage_time, on='sqlID', how='inner'
             )
             stage_times.info()
             sqls_to_drop = set(
@@ -1074,10 +1077,14 @@ def load_qtool_execs(qtool_execs: List[str]) -> Optional[pd.DataFrame]:
     if qtool_execs:
         exec_info = pd.concat([pd.read_csv(f) for f in qtool_execs])
         node_level_supp = exec_info.copy()
-        node_level_supp['Exec Is Supported'] = node_level_supp[
-            'Exec Is Supported'
-        ] | node_level_supp['Exec Name'].apply(
-            lambda x: any([x.startswith(nm) for nm in unsupported_overrides])
+        node_level_supp['Exec Is Supported'] = (
+            node_level_supp['Exec Is Supported']
+            | node_level_supp['Exec Name'].apply(
+                lambda x: any([x.startswith(nm) for nm in unsupported_overrides])
+            )
+            | node_level_supp['Exec Name'].apply(
+                lambda x: x.startswith('WholeStageCodegen')
+            )
         )
         node_level_supp = (
             node_level_supp[['App ID', 'SQL ID', 'SQL Node Id', 'Exec Is Supported']]
diff --git a/user_tools/src/spark_rapids_tools/tools/qualx/qualx_main.py b/user_tools/src/spark_rapids_tools/tools/qualx/qualx_main.py
index 043430328..25ace9c0f 100644
--- a/user_tools/src/spark_rapids_tools/tools/qualx/qualx_main.py
+++ b/user_tools/src/spark_rapids_tools/tools/qualx/qualx_main.py
@@ -21,7 +21,6 @@
 import pandas as pd
 import traceback
 import xgboost as xgb
-from importlib_resources import files as package_files
 from pathlib import Path
 from spark_rapids_tools.tools.qualx.preprocess import (
     load_datasets,
@@ -126,12 +125,14 @@ def _compute_summary(results):
         'Duration_supported',
         # actual
         'gpuDuration',
+        'xgpu_appDuration',
     ]
     cols = [col for col in result_cols if col in results.columns]
     # compute per-app stats
-    summary = (
-        results[cols].groupby(['appName', 'appId', 'appDuration']).sum().reset_index()
-    )
+    group_by_cols = ['appName', 'appId', 'appDuration']
+    if 'xgpu_appDuration' in results:
+        group_by_cols.append('xgpu_appDuration')
+    summary = results[cols].groupby(group_by_cols).sum().reset_index()
     if 'gpuDuration' in summary:
         summary['gpuDuration'] = summary['gpuDuration'].replace(0.0, np.nan)
 
@@ -153,9 +154,8 @@ def _compute_summary(results):
     # for datasets w/ labels, reconstruct actual speedup per-app
     # TODO: get this from actual CSV file?
     if 'y' in results:
-        summary['appDuration_actual'] = (
-            summary['appDuration'] - summary['Duration'] + summary['gpuDuration']
-        )
+        assert 'xgpu_appDuration' in summary
+        summary = summary.rename({'xgpu_appDuration': 'appDuration_actual'}, axis=1)
         summary['speedup_actual'] = (
             summary['appDuration'] / summary['appDuration_actual']
         )
@@ -199,6 +199,7 @@ def _predict(
             if 'y' not in results:
                 results['y'] = np.nan
                 results['gpuDuration'] = 0.0
+                results['xgpu_appDuration'] = 0.0
 
             # compute per-app speedups
             summary = _compute_summary(results)
@@ -222,7 +223,7 @@ def _read_dataset_scores(
     eval_dir: str
         Path to the output directory of a `qualx evaluate` run.
     score: str
-        Type of metric to report: MAPE, wMAPE.
+        Type of metric to report.
     granularity: str
         Aggregation level for metric: sql, app.
     split: str
@@ -263,7 +264,7 @@ def _read_platform_scores(
     eval_dir: str
         Path to the output directory of a `qualx evaluate` run.
     score: str
-        Type of metric to report: MAPE, wMAPE.
+        Type of metric to report
     split: str
         Name of data split to report: train, test, all.
     """
@@ -321,7 +322,9 @@ def models():
     """Show available pre-trained models."""
     available_models = [
         model.replace('.json', '')
-        for model in os.listdir(package_files('qualx').joinpath('models'))
+        for model in os.listdir(
+            Path(Utils.resource_path('qualx/models/xgboost'))
+        )
     ]
     for model in sorted(available_models):
         print(model)
@@ -830,7 +833,7 @@ def compare(
     previous: str,
     current: str,
     *,
-    score: str = 'wMAPE',
+    score: str = 'dMAPE',
     granularity: str = 'sql',
     split: str = 'all',
 ):
@@ -845,7 +848,7 @@ def compare(
     current: str
         Path to current evaluation results directory.
     score: str
-        Type of score to compare: 'MAPE' (default) or 'wMAPE'.
+        Type of score to compare: 'MAPE', 'wMAPE', or 'dMAPE' (default).
     granularity: str
         Granularity of score to compare: 'sql' (default) or 'app'.
     split: str