Whitepaper V: The Bridge-Task Battery Comparative Cognition Metrics for Differentiating Statistical Mimicry from Causal Reasoning in Artificial Intelligence

This paper introduces the Bridge-Task Battery, a comparative evaluation framework designed to isolate functional differences between probabilistic Large Language Models (LLMs) and a deterministic constraint-based reasoning architecture referred to as the Universal Logic Core (ULC v4.6). The study applies established paradigms from developmental psychology and comparative cognition—including the Trap-Tube task, the Blicket Detector, False Belief paradigms, and counterfactual physics reasoning—to evaluate whether an AI system relies on associative pattern matching or grounded causal derivation Core Objective The primary objective is to determine whether modern generative models demonstrate genuine causal reasoning or whether their outputs reflect high-fidelity statistical mimicry. The Bridge-Task Battery is designed to fracture surface-level correlations and force causal isolation, counterfactual simulation, and epistemic stability. This paper is published as an open experimental research artifact to invite scrutiny, replication, critique, and independent verification.