The busy beaver function $\text{BB}(n)$ describes the maximum number of steps that an $n$-state Turing machine can execute before it halts (assuming it halts at all). It is not a computable function because computing it allows you to solve the halting problem.
Are functions like $\text{BB}(n) \bmod 2$, or more generally $\text{BB}(n) \bmod m$ for a modulus $m$, computable? Computing these functions doesn't solve the halting problem, so the above argument doesn't apply.
Edit, 10/11/22: It is maybe worth linking here to Scott Aaronson's survey The Busy Beaver Frontier, which ends with the following:
Perhaps my favorite open questions about the Busy Beaver function were posed by my former student Andy Drucker. He asked:
Is BB (n) infinitely often even? Is it infinitely often odd? Is the set {n : BB (n) is odd} computable?
Currently, we know only that BB (2) = 6 is even, while BB (1) = 1, BB (3) = 21, and BB (4) = 107 are odd.
We could likewise ask: is BB (n) infinitely often prime? Is it infinitely often composite? (Right now one prime value is known: BB (4) = 107.) Is BB (n) ever a perfect square or a power of 2? Etc.
Of course, just like many of the questions discussed in previous sections, the answers to these questions could be highly sensitive to the model of computation. Indeed, it’s easy to define a Turing-complete model of computation wherein every valid program is constrained to run for an even number of steps (or a square number of steps, etc), so that some of these number-theoretic questions would be answered by fiat!
But what are the answers in “natural” models of computation, like Turing machines (as for the usual BB function), RAM machines, or Lisp programs?
Admittedly, these are not typical research questions for computability theory, since they’re so model-dependent. But that’s part of why I’ve grown to like the questions so much. Even to make a start on them, it seems, one would need to say something new and general about computability, beyond what’s common to all Turing-universal models — something able to address “computational epiphenomena,” like whether a machine will run for an odd or even number of steps, after we’ve optimized it for a property completely orthogonal to that question.