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Q: What value should I use for classiter ?

A: Large (4-8) values of classiter do an excellent job of preventing model/noise bias, but slightly degrade resolution
and sharpness (different things) of the reconstruction. I suggest using 4-8 for a few rounds until convergence, then
do your high resolution refinement with 3 (which actually does only 1 iteration for historical reasons). 3 is still
reasonably consevative with respect to inducing model bias. Then at the end, if you want to 'sharpen up' your
model again, you can use 0 for at most 2 iterations. In many cases you can continue to improve the resolution as
measured by FSC by iterating more with classiter = 0, but this is meaningless, as it's really just inducing
noise bias. One or (at most) two iterations of classiter=0 is reasonably safe at the very end of the process, but if you
want to have a little extra confidence that you can trust what you see, you might want to stick with 3 or more.