Table 2. Summary of the comparison between the observed BMR for mice under CR and the predicted BMR using the seven different predictive models.

Model	r2	Intercept	p(int)	Gradient	p(grad)
ONE	0.667	−0.697	p < 0.0005	2.294	p < 0.0005
TWO	0.667	−0.433	p < 0.0005	1.800	p < 0.0005
THREE	0.713	−0.667	p < 0.0005	2.431	p < 0.0005
FOUR	0.537	−0.035	p = 0.559	0.939	p = 0.77
FIVE	0.528	0.0367	p = 0.567	0.887	p = 0.38
SIX	0.554	0.0159	p = 0.800	0.927	p = 0.45
SEVEN	0.557	−0.051	p = 0.470	0.963	p = 0.84

R² is the correlation coefficient squared for the least squares fit regression, intercept is the intercept of the regression, p(int) is the probability that the intercept differs from 0 (t-test), Gradient is the gradient of the regression and p(grad) is the probability that the gradient differs from 1.0 (t-test). Parameters lists the parameters included in the predictive equations for the respective models. For details of the different predictive models refer to the methods and Figure S1 in Supplementary Materials.