Clarification on get_prior

Please also provide the following information in addition to your question:

  • Operating System: Windows 10
  • brms Version: 2.8

This might be a very basic question, but I realized I am a little confused about the output of get_prior().
So I used the get_prior() function for my model:

get_prior(bf(Y ~ 100 + (A-100) / (1 + exp ((B-t) / C)),
A~ 1 + (1|ID),
B ~ 1 + (1|ID),
C ~ 1,
nl = TRUE), data = Data)

The output I get from it is the following:


I am still a bit confused about what the meaning of Prior 2.
Why do we need Prior 2, if we have Prior 3? Do they not somehow express the same thing? Also, I am not sure I clearly understand the meaning of Prior 4 - standard deviation of the distribution of a population effect?
Or is Prior 2 somewhat of a combination of 3 and 4?

I read this, but I didn’t find anything about prior 4, and as to the other two, it seems like something similar to Prior 2 was explained for population effects, but then left me wondering about why we would need Prior 3.

Any help would be appreciated!

There are multiple threats in discourse here I believe that discuss the same issue (hierarchy in the prior specification in brms). Perhaps you find your question already answered.