  We demonstrate how a morphological veto involving Bayesian statistics can
improve the receiver-operating characteristic (ROC) curves of the current
search for core-collapse supernovae (CCSNe) as implemented by the coherent
Waveburst (cWB) algorithm. Examples involving two implementations of BayesWave
(BW), one that makes no assumption of the polarization state of the
gravitational wave (GW) and one that uses the same elliptical polarization
settings adopted in previous usages for Binary systems are provided on the set
of waveforms currently adopted for the first and second Advanced LIGO (aLIGO)
science runs for the targeted CCSNe search. A comparison of the performance for
all-sky searches versus the targeted searches with optical triggers is
provided. The average cWB+BW ROC range improvements with respect to a fixed
false-alarm rate (FAR) for slowly-rotating waveforms ranged from [+1.30%,
+15.76%] while the improvement for rapidly-rotating waveforms were on the order
of [+1.19%, +22.05%]. The application of BW to CCSN GW triggers also shows a
significant reduction of the FAR while maintaining detection efficiency and
remaining sensitive to a wide range of morphological CCSNe signals. It appears
that the code developed for arbitrarily polarized signals outperforms the
previous code for the GW morphologies tested.
