CogOS: From Gödel to AGI — Integrated Edition

[wAI ~ wErrors] «All models are wrong, but some are useful.» — George E. P. Box (1976) This preprint integrates CogOS, the mathematical companion “Ontology Refinement as Equivariant Coordinate Discovery,” the standalone “VKB-Training: Epistemic Metadata, Ontology Attention, and Cultural Compilers for Hallucination Reduction in Large Language Models,” S.V.E. IV/VIII/IX/X/XI/XII, the later “Metric Is Not a Metaphor” correction, and accompanying meaning-calibration, mathematical-review, hypothesis-backlog and prompt artifacts. Its central research thesis is that intelligence is not exhausted by optimization inside a fixed representation: a deeper capability is to detect representational failure, discover or construct better coordinates and concepts, preserve justified invariants across the transition, and verify the new representation against reality and counterevidence. The synthesis introduces an Intelligence Passport rather than a scalar intelligence score; an Ontology Commit / AtlasGit-style versioning model; a Living Intelligence Stack; a machine scientific-revolution benchmark; a freedom/non-totalization boundary for human-facing systems; local-subspace cultural compilers; and explicit interfaces to FSIM ontology CI, ANT/CANTGBoost, .antcolony/CANTGit, Verified Executable Knowledge, Phase/Clifford, Systemic Geometry Under Stress, Consequence Gap and S.V.E. Omega. The paper also narrows over-strong historical claims. Gödel’s incompleteness theorems do not by themselves prove semantic, ethical or theological conclusions; a learned ethical embedding is not a transcendent oracle; and geometric language earns scientific status only after the state space is specified, the metric is derived or operationalized, and novel quantitative predictions survive falsification. Highly speculative hypotheses (semantic Ricci flow, S3 consciousness, moral holonomy, theological Perelman analogies, etc.) are preserved in a typed registry rather than presented as established results. v1.2 additions VKB-Training is integrated as the epistemic-metabolism layer of the architecture. The synthesis retains its six-category taxonomy, four-stage annotation pipeline, confidence/provenance/BlindSpot/temporal/ontology mechanisms, cultural compilers, proposed experiment, open limitations, and ethical data-sourcing proposal, while adding technical corrections and four new bridges: (1) a factorized epistemic record separating epistemic role from ontology context; (2) a Causal Grounding Gate for intervention-sensitive representation validation; (3) a Semantic ABI for ontology migration without catastrophic forgetting; and (4) a Kernel Custody Protocol preventing the runtime from unilaterally certifying changes to its own invariant semantic core. It also introduces a verification-scaling frontier and expands the decisive experiment queue to 42 research cards. Evidence boundary / notes The core CogOS architecture is theoretical; source documents explicitly state that empirical validation is incomplete or absent for many claims. AI-generated examples and AI dialogue are treated as hypothesis-generation material, not independent empirical evidence. The Christian/Christological layer is retained as a declared theological profile and research hypothesis where appropriate; it receives no automatic mathematical privilege. The “Metric Is Not a Metaphor” supplement governs the geometry scope: specify state space, derive/operationalize metrics, and issue falsifiable quantitative predictions. No person-level moral or dehumanization score is proposed. No literal self-harm or human self-sacrifice experiment is proposed; the systems analogue is bounded costly self-limitation, abstention, rollback, or shutdown. Suggested related identifiers / works S.V.E. Omega: The Self-Obsoleting Verification Stack (companion synthesis) FSIM: The Open Door v1.2 (ontology CI / epistemic contracts) Verified Executable Knowledge (ANT/CANT synthesis) Phase Algebra V: The Epistemic Engine Systemic Geometry Under Stress v1.1 CANTGBoost: https://huggingface.co/skovnats/CANTGBoost CANTGBoost Zenodo: https://doi.org/10.5281/zenodo.21699806 ANT record: https://doi.org/10.5281/zenodo.21628614 S.V.E. Meta-License: https://doi.org/10.5281/zenodo.19373736 VKB-Training. S.V.E. Meta-License v5.0