  We present a new automated method to identify instrumental features
masquerading as small, long period planets in the \kepler\ planet candidate
catalog. These systematics, mistakenly identified as planet transits, can have
a strong impact on occurrence rate calculations because they cluster in a
region of parameter space where Kepler's sensitivity to planets is poor. We
compare individual transit-like events to a variety of models of real transits
and systematic events, and use a Bayesian Information Criterion to evaluate the
likelihood that each event is real. We describe our technique and test its
performance on simulated data. Results from this technique are incorporated in
the \kepler\ Q1-17 DR24 planet candidate catalog of \citet{Coughlin15}.
