Softmax over logits doesn’t give calibrated probabilities either as a rule. I don’t want to comment specifically on Jev but as a rule it’s very hard to get good calibration because it’s somewhat in tension with minimizing training loss for neural networks, e.g. Guo et al (2017) https://arxiv.org/abs/1706.04599

While I know there are ways to improve calibration, I’d personally want to see a lot of evidence the probabilities were actually more meaningful before trusting them. I agree of course that asking an LLM to provide a confidence estimate is meaningless.