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This paper introduces the Cognitive Kernel Model (CKM), a prompt-level state-enforcement layer that forces large language models to separate fact, heuristic, and emotion before making decisions. Experiments on 26 LLMs show CKM reduces output variability and decision flipping without changing model weights.