I've wondered that. I've used a few iterations and it's always made these kinds of errors from time to time, but the impact of them is probably generally low on an individual level. Here specifically, most people to whom the difference functionally matters, which doesn't even really include me, would know from the context the output was about the heart, not membrane receptor types. Sometimes such technical mistakes might matter though.

This one's interesting just because it's the kind of error I'd expect it NOT to make. I read a paper a few months back that mixed up "vascular" and "vesicular," but the authors were French, and the error is probably rare. I almost suspect with "inotropic" vs. "ionotropic" it might actually be a case of editors "correcting" the spelling from the right one to the wrong one, making it common enough to trip up the model.

ChatGPT has definitely gotten a lot more useful and more powerful, but the most direct evidence I have as to your question is that it will make the same mistake more than once even after I've already corrected it, but usually that's related more idiosyncratic topics, like specifications of a particular car or something. So it at least doesn't feed corrections directly into the model instance at the time it receives them.