Neil wrote:
>
> So maybe this is moving slightly off on a tangent, but:
> Why does auto-learn sometimes learn spam with a rating of X, but not
> spam with a rating of X+Y? Where's it's methodology?


First, there's several rules involved here.

To autolearn as spam *ALL* of the following must be met:

-must have at least 3 points from header type rules
-must have at least 3 points from body type rules
-must not already match a low-scoring bayes rule in the existing
training (ie: BAYES_00) This prevents autolearning from contradicting
existing training.
-After recomputing the score of the message as if bayes and all userconf
rules were disabled (including changing the scoreset! This makes a big
difference in some cases.), that score must be over the spam learning
threshold. This prevents bayes from engaging in self-feedback or
feedback based on manual whitelists (which, if misconfigured would cause
a "bayes hangover" of mis-learned mail).

Generally speaking, the score you see in the message header has only a
loose correlation with the score used for learning checks.