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This paper empirically studies Jev, a decision-oriented "System One Model," for personalized recommendation reranking, finding it occupies a distinct quality–latency operating regime compared with recommendation-specific models and pointwise/listwise LLM rerankers across multiple domains and candidate-set sizes.