This paper describes one phase of a large-scale machine translation (MT) quality assurance project. We explore a novel approach to discriminating MT-unsuitable source sentences by predicting the expected quality of the output. The resources required include a set of source/MT sentence pairs, human judgments on the output, a source parser, and an MT system. We extract a number of syntactic, sema...