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The automatic prediction of protein three-dimensional structures from an amino acid sequence has become one of the most important and researched fields in bioinformatics. As models are not experimental structures determined with known accuracy but rather with prediction, it is vital to determine estimates of a model's quality.  We attempt to solve this problem using machine learning techniques and information from both the sequence and structure of the protein.