[phenixbb] How to reduce clashscore value

[Pavel Afonine]

> The likelihood function can then be plugged in to Bayes' law - if the 
> model and data error terms are all accounted for, no other weighting 
> should be necessary.

If I arbitrarily multiply the ML function (or any other - doesn't 
matter) by 100, the weight will have to account for this. The one based 
on ratio of gradient norms (or any other of similar kind) will do. Given 
the amount and variety of targets (both, data and restraints) we need to 
deal with (because each model and data quality require adequate proper 
parametrization), this flexibility is very essential. Postulating 
introduces rigidity, and that doesn't help to sample space when doing 
optimization.

Pavel