  In this paper we describe how crowd and machine classifier can be efficiently
combined to screen items that satisfy a set of predicates. We show that this is
a recurring problem in many domains, present machine-human (hybrid) algorithms
that screen items efficiently and estimate the gain over human-only or
machine-only screening in terms of performance and cost.
