diff --git a/mlair/plotting/postprocessing_plotting.py b/mlair/plotting/postprocessing_plotting.py
index 6e9a2a401f2990fe1fa7cfddf8711f37eda4bf48..5cc449aac88ebab58689656820769fe7751f6098 100644
--- a/mlair/plotting/postprocessing_plotting.py
+++ b/mlair/plotting/postprocessing_plotting.py
@@ -711,6 +711,8 @@ class PlotBootstrapSkillScore(AbstractPlotClass):
         """
         data = helpers.dict_to_xarray(data, "station").sortby(self._x_name)
         self._labels = [str(i) + "d" for i in data.coords["ahead"].values]
+        if "station" not in data.dims:
+            data = data.expand_dims("station")
         return data.to_dataframe("data").reset_index(level=[0, 1, 2])
 
     def _label_add(self, score_only: bool):
diff --git a/mlair/run_modules/model_setup.py b/mlair/run_modules/model_setup.py
index 8a2951ef336680b9515b1f6538ab3190ef61035c..3dc56f01c4f37ce9fc53086d837386af81e5f53d 100644
--- a/mlair/run_modules/model_setup.py
+++ b/mlair/run_modules/model_setup.py
@@ -165,7 +165,7 @@ class ModelSetup(RunEnvironment):
                 v = ",".join(self._clean_name(str(u)) for u in v)
             if "<" in str(v):
                 v = self._clean_name(str(v))
-            df.loc[k] = v
+            df.loc[k] = str(v)
         df.sort_index(inplace=True)
         column_format = "ll"
         path = os.path.join(self.data_store.get("experiment_path"), "latex_report")
diff --git a/mlair/run_modules/post_processing.py b/mlair/run_modules/post_processing.py
index c781d593d9bf8d8747ebc823fc15038c083ac81a..da76d939ae0e8a09a517be400c08686d1e9b184d 100644
--- a/mlair/run_modules/post_processing.py
+++ b/mlair/run_modules/post_processing.py
@@ -74,7 +74,7 @@ class PostProcessing(RunEnvironment):
         self.plot_path: str = self.data_store.get("plot_path")
         self.target_var = self.data_store.get("target_var")
         self._sampling = self.data_store.get("sampling")
-        self.window_lead_time = extract_value(self.data_store.get("output_shape", "model"))
+        self.window_lead_time = extract_value(self.data_store.get("shape_outputs", "model"))
         self.skill_scores = None
         self.bootstrap_skill_scores = None
         self._run()
@@ -217,7 +217,7 @@ class PostProcessing(RunEnvironment):
                     skill.loc[boot_var] = np.array(boot_scores)
 
                 # collect all results in single dictionary
-                score[station] = xr.DataArray(skill, dims=["boot_var", "ahead"])
+                score[str(station)] = xr.DataArray(skill, dims=["boot_var", "ahead"])
             return score
 
     @staticmethod
diff --git a/mlair/run_script.py b/mlair/run_script.py
index a4451c6bda3cea1d6e1f433750984d1e40b583f0..aa197190637bdb93a49c0ad2febc27414e305662 100644
--- a/mlair/run_script.py
+++ b/mlair/run_script.py
@@ -39,6 +39,6 @@ def run(stations=None,
 
 
 if __name__ == "__main__":
-    from src.model_modules.model_class import MyBranchedModel
-    run(stations=["DEBW013","DEBW025"], statistics_per_var={'o3': 'dma8eu', "temp": "maximum"}, trainable=True,
+    from mlair.model_modules.model_class import MyBranchedModel
+    run(statistics_per_var={'o3': 'dma8eu', "temp": "maximum"}, trainable=True,
         create_new_model=True, model=MyBranchedModel)