our models and treat all of this data as a kind of extended version of our label data and users to the labels in our subsequent training yeah before before speaking of how to with how could we utilize to the labels I'll talk about some kind of couple of ingredients the first one is confidence so instead of taking all the predictions from the code test set we're interested only in the content predictions the reason for that is if we add to power of two the labels some observations that are hard to predict or some special cases some