approximately 600 so so the fact is like we don't have a lot of negatives but all these negatives are really hard because they're coming from other practices within the same image so it's it's a mix of like instance negatives as for the spacial negatives and it learns both kind of discriminative features so this is basically a diagram that illustrates this whole pipeline where you perform you you you have this feature extractor which is the rest net1 61 running on patches of images and you train the cells provision objective which is CPC