diff --git a/configs/ref_quantile_lgbm.yaml b/configs/ref_quantile_lgbm.yaml
index 7653c2df..59987d27 100644
--- a/configs/ref_quantile_lgbm.yaml
+++ b/configs/ref_quantile_lgbm.yaml
@@ -44,7 +44,7 @@ learning:
 
 prediction:
   prediction_template: configs/data/sirsam/dem_foc2.tif
-  quantiles: 0.90
+  quantiles: 0.9
   outbands: 4
 
 
diff --git a/uncoverml/predict.py b/uncoverml/predict.py
index 640534bf..ca054a35 100644
--- a/uncoverml/predict.py
+++ b/uncoverml/predict.py
@@ -22,7 +22,7 @@
 
 
 def predict(data, model, interval=0.9, **kwargs):
-
+    log.debug(f"Supplied prediction quantiles {interval}")
     # Classification
     if hasattr(model, 'predict_proba'):
         def pred(X):
@@ -36,6 +36,11 @@ def pred(X):
             if hasattr(model, 'predict_dist'):
                 if hasattr(model, 'upper_alpha') and hasattr(model, 'lower_alpha'):
                     interval = model.upper_alpha - model.lower_alpha
+                    print("====in predict====", model.upper_alpha, model.lower_alpha, interval)
+                    log.warn(f"As upper and lower alpha are both specified, "
+                             f"we used interval = model.upper_alpha - model.lower_alpha."
+                             f" We ignored prediction.quantiles and used {interval}")
+
                 Ey, Vy, ql, qu = model.predict_dist(X, interval, **kwargs)
                 predres = np.hstack((Ey[:, np.newaxis], Vy[:, np.newaxis],
                                      ql[:, np.newaxis], qu[:, np.newaxis]))