Mmm ,
Um. And y
Yeah , yeah.
y  Right ? And then um  then see ,  again , how  We know that there 's a mis there 's a uh  a  a loss in performance when the neural net is trained on conditions that are different than  than , uh we 're gonna test on , but well , if you look over a range of these different tests um , how well do these different ways of combining the straight features with the MLP features , uh stand up over that range ?