made desc more user friendly

app.py

@@ -23,6 +23,8 @@ recall.compute()
 
 where the `average` parameter can be chosen to configure the way recall scores across labels are averaged. Acceptable values include `[None, 'micro', 'macro', 'weighted']` (
 or `binary` if there exist only two labels). \n
+
+Play around with the interface below to see how the recall score changes based on predictions, references, and method of averaging!
 """
 
 metric = FixedRecall()

fixed_recall.py

@@ -12,7 +12,7 @@ The recall is intuitively the ability of the classifier to find all the positive
 """
 
 _CITATION = """
-@online{MarioBbqRecall,
+@online{MarioBbqRec,
   author = {John Graham Reynolds aka @MarioBarbeque},
   title = {{Fixed Recall Hugging Face Metric},
   year = 2024,