If you can read between the lines, that says that there's no actual "judgement" going on. If there was a strong logical underpinning to the output, minor differences in input like the phrasing (but not factual content) of a prompt wouldn't make the quality of the output unpredictable.
Humans display biases very similar to that of LLMs. This is not a coincidence. LLMs are trained on human-generated data. They attempt to replicate human reasoning - bias and all.
There are decisions where "strong logical underpinning" is strong enough to completely drown out the bias and the noise. And then there are decisions that aren't nearly as clear-cut - allowing the bias and the noise to creep into the outcomes. This is true for human and LLM "judgement" both.