Can previous and continuing research on N-piece tablebases be used toward human theory of chess?

Question

This follows another questions here: What is the status for EIGHT piece endgame tablebases?

My answer there was appropriately removed as being question in reaction to that question, well in light of the question. So here is that non-answer, modified to be a question. I wish it to be considered with the above link in mind, as this previous question follows the existing expansion from 3 men to 7 men. As if it was the only way to use such information database scheme (the work is more than the tables we use).

Is there some machine learning approach that would use existing TBs and dissect their nesting statistically properties for clues of "nested" patterns?

I find that we might be waiting for computer power to do the exact retrograde, why not looking for more human ways of finding retro gradable, human theories of chess, that might be corroborated by information contained in some subsets of the TBs.

I find that, as humans, we actually started learning chess, each of us, on some naked board, one piece at a time. Why some jump to 32 right away? I forgot. But now I am seeing endgames, and compositions around them (TB is not just legal chess positions from standard IC), as research or study challenge that can stretch our reasoning to understand the un-stretched.

** So not just practical endgames, but games that allow both rational theory building from the spatial logic likely contained in the human created finite ruleset of chess, and also our experience. With an intrinsic pool of player independent referential "basis" of data, pure chess information. Not a statistical pairing outcome extrinsic accuracy measure. We have microscopic ruler. We don't have to follow it blindly, but we have that, being exact, we can approximate from there, do all sorts of data analysis or ML feature reduction transformations to test logical reasoning hypotheses or even suggest relations to investigate rationally, that can be controlled and characterized back to that level.

I find that from a chess science (not data hoarding), point of view, there might be untapped human accessible clusters of information from already existing from 3 chessmen up.. 3 to 7, that is four nesting levels.

I also know that there have been attempts to compress with Lc0 NN, up to the 6 men EGTB, as is (i.e. full TB, even that which might not be legal, just saying there is that chess, and there is human chess, not all about combinatorial turn by turn retrograde, and that is still logical, using spatial abstractions that consider that not every distinct position is equally distant w.r.t. to their solutions construction, itself not only accessible from turn-by-turn lowest logic. This might be a different kind of chess complexity, not having any chess words going for it, and not much computer terminology either, which is based on every distinct position being distinct equally. (not having the embedding to see any other angle).

I can improve on the question, upon feedback. The point here is about extracting more than oracle value from EGTB chess board analytical tool. As we have visuo-spatial abilities that are not put to work. Individually, there have been specific problems of chess or endgame classes that might have work on extracting such information, but it has not been very methodological as far as I could be made aware so far. Perhaps here, we could gather such attempts, if my top question, is a bit premature.