TABLE I.

Impact of each generalization class on performance. Accuracy values provide an estimate of the difficulty of that class after accounting for the random effects of individual mice. Accuracies are logistic GLMM coefficients transformed from logits, and model coefficients are logit differences from training set accuracy, which was used as an intercept. Correlation values are between fixed effects (novelty classes) across random effects (mice). *Indicates significance $(p(>\left|z\right|)\ll 0.001)$.

	Accuracy	95% Wald CI	Corr
Learned	0.767*	[0.748, 0.785]
Token	0.739*	[0.713, 0.763]	0.50
Vowel	0.678*	[0.655, 0.701]	0.81	0.91
Speaker	0.666*	[0.651, 0.680]	0.98	0.68	0.92
Vow+Spk	0.637*	[0.624, 0.651]	0.98	0.64	0.90	1