This is likely because the individual measures being averaged like "femur length" were not independent from one-another, even where they had the benefit of being normally distributed.
In fact, I find no meaningful difference between "But no _individual_ speaks like this." and "But the ratio was never the danger.", aside from them being about different topics. They are syntactically very similar.
It's a foundational model (fresh from autoregressive pretraining) that approximates the probability distribution of human texts. And, no, it's not the statistical average of how people speak. It approximates how a person who could have written a text in its context would have written the next words.
Fine-tuning, RLHF, reinforcement learning change this probability distribution. I guess, it's mostly RLHF that shapes the way LLMs write. The similarity of style is due to common providers of RLHF data.
If we assume that it is LLM generated, as suggested, apparently a lot of people, as the LLMs were trained to mimic how people speak (write).
You might find it to be unusual because you probably have never read anything written by most people. Only peculiar characters tend to get noticed.