Yes, but the prediction is itself encoding that it's a strong signal.
Meaning that, if given a context (prompt), it predicted that "the sky is blue", that's because the sky being blue is a stronger signal under that context - statistically speaking.
My point was that i feel like humans have these two aspects, the ability to have a fact, and the ability to have a signal to the facts strength. I propose that as an explanation why we can internally analyze our understanding and come to a conclusion that yes, we do "know" it.
We also at times can't figure out how we "know" it, either because we've made up a detail (filling in blanks, assumptions, etc), or because we forgot where we embedded this detail. The lower the signal strength of this validation the more we can be unsure about a "fact".
I feel like LLMs are one half, but not the other. They effectively need a RAG for all of the knowledge they have, and if the counter for a given fact/idea/etc is low enough, then it's an low signal.
The question i have is how to do this efficiently. Of course i'm just speculating too, i don't know any of this.