You might be surprised. Many students who use ChatGPT for assignments end up turning in code identical (or nearly identical) to other students who use ChatGPT.
Different in an exact string match but code that is copied and pasted from ChatGPT has a lot of similarities in the way that it is (over) commented. I've seen a lot of Python where the student who "authored" it cannot tell me how a method works or why it was implemented despite having the comments prefixed to every line in the file.
From my experience using ChatGPT, It usually remove most of my already written comments when I ask questions about code I wrote myself. It usually give you outline comments. So unless you are supporter of the self documented code idea, I don't think ChatGPT over comments.
It's obviously down to taste, but what I've seen over and over is a comment per line which to me is excessive outside it being requested of absolute beginners.
That happens and also the model can't decide if it wants the comment on the line before the code or if everything should be appended to the line itself so when I see both styles within a single project it's another signal. People generally have a style that they stick with.
yeah but the prompt itself generally adds sufficient randomness to avoid the same verbatim answer each time.
as an example just go ask it to write any sufficiently average function. use different names and phrases for what the function should do; you'll generally get a different flavor of answer each time, even if the functions all output the same thing.
sometimes the prompt even forces the thing to output the most naive implementation possible due to the ordering or perceived priority of things within the requesting prompt.
it's fun to use as a tool to nudge it into what you want once you get the hang of the preconceptions it falls into.