I would consider feature complete with robust testing to be a great proxy for code quality. Specifically, that if a chunk of code is feature complete and well tested and now changing slowly, it means -- as far as I can tell -- that the abstractions contained are at least ok at modeling the problem domain.

I would expect code that continually changes and deprecates and creates new features is still looking for a good problem domain fit.

It's tricky, but one can assume that code written once and not touched in a while is good code (didn't cause any issues, performance is good enough, ecc).

I guess you can already derive this value if you sum the total line changed by all PRs and divide it by (SLOC end - SLOC start). Ideally it must be a value slightly greater than 1.

It depends on how well you vetted your sanples.

fyi: You headline with "cross-industry", lead with fancy engineering productivity graphics, then caption it with small print saying its from your internal team data. Unless I'm completely missing something, it comes of as a little misleading and disingenuous. Maybe intro with what your company does and your data collection approach.