How Reducing Dynamic Range by Boosting Signal Improves Burst Detection?

I was given Matlab code to process a signal file. I do not have any details as to the ADC specs or the code's author. The variable, cxSamps (complex double), contains the signal's IQ data read from the entire file.

I see this line of code:

cxSamps  = cxSamps / mean( abs(cxSamps ) );


The comment says that this boosting of the cxSamps is to estimate a coarse AGC and that it is applied to the entire cxSamps. It reduces the dynamic range in order to help distinguish energy bursts from the noise.

1. how boosting the signal reduces the dynamic range?
2. how this improves identifying bursts in the noise?

Before:

mean( abs(cxSamps ) ) = 0.0052
min( abs(cxSamps) ) = 1.056e-06
max( abs(cxSamps) ) = 0.0343
20*log10( 0.0343 / 1.056e-06 ) = 90.231


After:

mean( abs(cxSamps ) ) = 1 (no surprise)
min( abs(cxSamps) ) = 2.03e-04
max( abs(cxSamps) ) = 6.5877
20*log10( 6.5877/ 2.03e-04) = 90.226


I reviewed this: Ref: Compute dynamic range in a linear quantization system

EDIT
I believe the above Before and After calculations now have no bearing on my question since I now realize that the dynamic range is just a function of the ADC number of bits.

I don't think the comment is correctly describing what is happening. Just scaling the entire data set by a constant value, in this case mean(abs(cxSamps)), shouldn't change the dynamic range as the largest and smallest values will be scaled by the same amount.