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This paper formalizes the problem of ordering filters in sequential filtering pipelines under independent cost and selectivity models, proving that ordering by increasing ratio of cost to rejection probability is optimal. Monte Carlo simulations demonstrate that this ordering dominates common heuristics both in expectation and across the full distribution of outcomes.