See the graphs in the paper that introduced nucleus sampling: The Curious Case of Neural Text Degeneration. They visualize how human authored text has different statistical properties from machine generated text. That's mainly a tradeoff between fluency and coherence. Sampling procedures like top-k or nucleus sampling restrict the tokens that can be emitted and thus introduce statistical bias in the generated text, but produce more fluent text. Rather, sampling from the full distribution gets closer to the distribution of human-authored text, but often degenerates into incoherence (hence the title of the paper).