Now this is what I have so far but no learning is happening. is this correct?
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tflags BAYES_999 learn
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# read for scores: /var/lib/spamassassin/3.004001/updates_spamassassin_org/60_shortcircuit.cf
# read for details: https://spamassassin.apache.org/full/3.4.x/doc/Mail_SpamAssassin_Plugin_Shortcircuit.html
# Shortcircuit - stop evaluation early if high-accuracy rules fire
#
loadplugin Mail::SpamAssassin::Plugin::Shortcircuit
# Some shortcircuiting, if the plugin is enabled
#
ifplugin Mail::SpamAssassin::Plugin::Shortcircuit
#
# default: strongly-whitelisted mails are *really* whitelisted now, if the
# shortcircuiting plugin is active, causing early exit to save CPU load.
# Uncomment to turn this on
#
# shortcircuit USER_IN_WHITELIST on
# shortcircuit USER_IN_DEF_WHITELIST on
# shortcircuit USER_IN_ALL_SPAM_TO on
# shortcircuit SUBJECT_IN_WHITELIST on
# the opposite; blacklisted mails can also save CPU
#
# shortcircuit USER_IN_BLACKLIST on
# shortcircuit USER_IN_BLACKLIST_TO on
# shortcircuit SUBJECT_IN_BLACKLIST on
# if you have taken the time to correctly specify your "trusted_networks",
# this is another good way to save CPU
#
# shortcircuit ALL_TRUSTED on
# and a well-trained bayes DB can save running rules, too
#
shortcircuit BAYES_999 spam
tflags BAYES_999 learn
# shortcircuit BAYES_99 spam
# shortcircuit BAYES_00 ham
endif # Mail::SpamAssassin::Plugin::Shortcircuit
# Not needed for now but no idea how exactly to change this.
# The default Shortcircuit spam score is 100 while ham is -100.
# These scores may be altered with the "shortcircuit_spam_score" and
# "shortcircuit_ham_score" variables.
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shortcircuit BAYES_999 spam
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tflags TEST noautolearn
spam
Shortcircuit the rule using a set of defaults; override the default score of this rule with the score from shortcircuit_spam_score, set the noautolearn tflag, and set priority to -100. In other words, equivalent to:
shortcircuit TEST on
priority TEST -100
score TEST 100
tflags TEST noautolearn