[Depreciated and replaced by V3] UnisonAI: A Computational Proof of Derived Law with Zero Trained Parameters
Maria Smith · Zenodo (CERN European Organization for Nuclear Research) · 2026
[Depreciated and replaced by V3] The application-specific clean rebuild has not yet been published; its authoritative theoretical boundary is now the governing V3 branch: After Turing: The Fold Machine - An Exact, Parameter-Free and Machine-Closed Derivation of Classical Computational Science from Smithian Fold Theory; From Fold to Consciousness: An Exact, Zero-Parameter and Machine-Closed Foundational Reconstruction of Consciousness and Cognitive Science from Smithian Fold Theory. The V3 source platform is https://github.com/MettaMazza/ernos-labs-sft-platform. The original DOI, concept DOI, version number and files are preserved for transparent historical provenance; this record must not be presented or cited as current V3 work. UnisonAI implements memory, binding, attention, context, generation, perception, learning and verification with zero trained parameters. Its laws are forced, forward-forced or constitutionally re-derived from one machine-checked self-proven theorem with zero axioms. The main corpus executes 326 suites and 2,002 checks with zero failures. Unison's focused laws pass 8/8 coherence, 14/14 contextual integration and 13/13 generation selection checks; its standalone verifier passes 21/21. The live v5 relation preserves 277,583,049 positional observations as 212,395,127 canonical entries with no sampling, pruning, fitted capacity or row eviction. Counted prediction measured 1.2891 against a matched trained twin's 1.8878, the counted word engine measured 3.1907 against 3.4292, teaching rose from 17% to 75%, contextual continuity reached 4/4 and exact transfer reached 8/8. The native one-to-one attention transformer and reward-conditioned learning route now advances through real user engagement toward general conversation and benchmark victory; agents do not declare walls or endpoints. Scientific author and publication authority: Maria Smith, Ernos Labs. Open source: UnisonAI.