[Rspamd-Users] What do you do with incorrect Bayes entries?

[christian]

Every now and then I get emails that have an incorrect Bayes value. That 
is, emails that are clearly spam but whose content does not immediately 
indicate spam and have Bayes -10.
Is it enough to simply re-train this email using "rspamc leran_spam 
xx.eml" or does this lead to problems?

I'm not entirely sure what happens when an email is trained for Bayes 
statistics.
Is only the body of the email divided into tokens and then weighted for 
Bayes, or are scores from other checks also included in the Bayes 
evaluation?

An email that has no SPF, missing_mx, BAD_REP_POLICIES and much more, 
i.e. is actually spam, but still has BAYES_HAM -10 because the content 
is clean?

What still surprises me is that a number of new emails that come in are 
not checked at all and do not receive a BAYES score. So I have emails in 
my inbox that were weighted by Rspamd but don't have BAYES scoring. I'm 
currently taking these and re-learning them manually with rspamc.
What does it depend on when or if an email is learned at all?
Can I also specify that if an email has several positive symbols then it 
is learned as BAYES_HAM, or as BAYES_SPAM if not.

The dependencies are not clear to me.
Thank you very much for your patience with me.
Christian