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Logical Uniqueness in Generative AI — The Fixation of the Pre-Judgment Structure as a Necessary Condition —
This paper examines why generative AI systems produce different outputs for identical inputs. Rather than treating this as a matter of probabilistic behavior or model accuracy, the study analyzes it as a structural condition of judgment formation. It argues that logical output uniqueness requires the prior fixation of pre-judgment structures, and clarifies the conditions under which non-unique outputs structurally arise in generative AI systems.
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