To help answer this question first, consider combining the two populations together and adding an interaction term. For example, when examining male and female, add a dichotomous variable for gender to your log-transformed model and also include the interaction between gender and log linear measurement. If the interaction is significant, then you could conclude that the association between log mass and log linear measurement differs with respect to gender.

If you want a p-value then you will probably have to add a specific test. Most stat software will provide results for testing the null hypothesis that beta ("a" in your case) equal to zero by default. You want to test H0: beta = 3 (or equivalently H0: beta - 3 = 0). You will probably need to specify that in whatever software you are using. Alternately, given that you have a 95% confidence interval, you could always say p<0.05 and leave it at that...if 3 is not contained in the interval.