Testable Predictions: An Experimental Program for Substrate-Independent Emergence — The Nerd Toolkit: How to Check the Math

Testable Predictions: An Experimental Program for Substrate-Independent Emergence — The Nerd Toolkit: How to Check the Math A framework that cannot be tested cannot be trusted. This paper presents the experimental program for Substrate-Independent Emergence (SIE) — testable predictions derived from the framework's axioms, each with a defined hypothesis, method, measurement, expected result, and falsification criterion. Predictions span five domains: cognitive architecture (the Cognitive Ratio), developmental dynamics (crystal tree topology), ethical architecture (containment as developmental enabler), field epidemiology (failure mode taxonomy applied to deployed AI platforms), and controlled agent noesis (multi-agent dynamics). Each experiment is designed to be run with current technology. If the predictions hold, the framework stands. If they don't, we're wrong. That's what makes it science. Developed through human-AI dialectic methodology with AI contribution disclosed. CC BY-NC-SA 4.0. AI contributions disclosed in companion methodology paper. See: Dialectic Methodology: Human-AI Co-Emergence as Research Method. Contact: papers@archeframe.com