  Almost four decades ago, Gacs, Kurdyumov, and Levin introduced three
different cellular automata to investigate whether one-dimensional
nonequilibrium interacting particle systems are capable of displaying phase
transitions and, as a by-product, introduced the density classification problem
(the ability to classify arrays of symbols according to their initial density)
in the cellular automata literature. Their model II became a well known model
in theoretical computer science and statistical mechanics. The other two
models, however, did not receive much attention. Here we characterize the
density classification performance of Gacs, Kurdyumov, and Levin's model IV, a
four-state cellular automaton with three absorbing states---only two of which
are attractive---, by numerical simulations. We show that model IV compares
well with its sibling model II in the density classification task: the
additional states slow down the convergence to the majority state but confer a
slight advantage in classification performance. We also show that,
unexpectedly, initial states diluted in one of the nonclassifiable states are
more easily classified. The performance of model IV under the influence of
noise was also investigated and we found signs of an ergodic-nonergodic phase
transition at some small finite positive level of noise, although the evidences
are not entirely conclusive. We set an upper bound on the critical point for
the transition, if any.
