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We present a mathematical framework for assessing the quality of signature systems in terms of fidelity, risk, cost, other attributes, and utility-a method we call Signature Quality Metrics (SQM). We demonstrate the SQM approach by assessing the quality of a signature system designed to predict the culture medium used to grow a microorganism. The system consists of four chemical assays and a Bayesian network that estimates the probabilities the microorganism was grown using one of eleven culture media. We evaluated fifteen combinations of the signature system by removing one or more of the assays from the Bayes net. We show how SQM can be used to compare the various combinations while accounting for the tradeoffs among three attributes of interest: fidelity, cost, and the amount of sample material consumed by the assays.