Somebody outside of LW asked how to quantify prior knowledge about a thing. When googling I came across a mathematical definition of surprise, as "the distance between the posterior and prior distributions of beliefs over models". So, high prior knowledge would lead to low expected surprise upon seeing new data. I didn't see this formalization used on LW or the wiki, perhaps it is of interest.

Speaking of the LW wiki, how fundamental is it to LW compared to the sequences, discussion threads, Main articles, hpmor, etc?