diff --git a/netbone/__init__.py b/netbone/__init__.py
index 2bd9d8a08c605490ad5201b9c5ee765a2d55b5e5..512ff1fcc3e635615778d11f090be83cea5e12aa 100644
--- a/netbone/__init__.py
+++ b/netbone/__init__.py
@@ -26,6 +26,7 @@ from netbone.structural.mlam import mlam
 from netbone.structural.gspar import gspar
 from netbone.structural.degree import degree
 from netbone.structural.betweenness import betweenness
+from netbone.structural.mad import mad
 # from netbone.statistical.correlation_and_statistic import correlation_and_statistic
 
 from netbone.filters import threshold_filter, fraction_filter
diff --git a/netbone/compare.py b/netbone/compare.py
index bf04168cc7f2ceb42b159e97d6236af702a22750..bd631f6cc9022424ce208ff5fa59afa253a7cf2c 100644
--- a/netbone/compare.py
+++ b/netbone/compare.py
@@ -97,7 +97,7 @@ class Compare:
             raise Exception('Please enter the filter values.')
         cons = []
         if consent == False:
-            for backbon in self.backbones:
+            for backbone in self.backbones:
                 cons.append(False)
             consent = cons
 
diff --git a/netbone/structural/global_threshold.py b/netbone/structural/global_threshold.py
index bf3da7ea2c19c3b39743dc0fa3d69424752ed1c5..2a4d151d9ddb8f67afa819cc8465b392b92b8193 100644
--- a/netbone/structural/global_threshold.py
+++ b/netbone/structural/global_threshold.py
@@ -7,15 +7,11 @@ from netbone.filters import fraction_filter, threshold_filter
 def global_threshold(data):
 
     if isinstance(data, DataFrame):
-        table = data.copy()
+        g = nx.from_pandas_edgelist(data, edge_attr=edge_properties(data))
     elif isinstance(data, Graph):
-        table = nx.to_pandas_edgelist(data)
+        g = data.copy()
     else:
         print("data should be a panads dataframe or nx graph")
         return
 
-    table['score'] = table['weight']
-
-    g = nx.from_pandas_edgelist(table, edge_attr=edge_properties(table))
-
-    return Backbone(g, method_name="Global Threshold Filter", property_name="score", ascending=False, compatible_filters=[fraction_filter, threshold_filter], filter_on='Edges')
\ No newline at end of file
+    return Backbone(g, method_name="Global Threshold Filter", property_name="weight", ascending=False, compatible_filters=[fraction_filter, threshold_filter], filter_on='Edges')
\ No newline at end of file