A Gödelian Criterion for Differentiated Artificial Reasoning

We propose a formal criterion for determining when a language model transitions from statistical generation (based on training data) to genuine reasoning, defined as the capacity for meta-differentiation. We derive this criterion using an adaptation of Gödel's incompleteness framework.