interesting behaviors with respect to the developments of how it's labeling each of these data points and see if our 10 data set throughout the training you see that it the label with the highest confidence doesn't change it doesn't get steeper between 50 and 75 percent it doesn't do things like flipping labels or dampening distributions in obvious ways that are typically heuristically explored with respect to you know doing regularization in the class label space another interesting algorithm in the space of meta learning these different