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Record W7087797040 · doi:10.5281/zenodo.17313453

aluisayala/the-real-scope-of-omega: The Real Scope of Ω

2025· other· en· W7087797040 on OpenAlexaff

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2025
Typeother
Languageen
FieldComputer Science
TopicComputability, Logic, AI Algorithms
Canadian institutionsOttawa Public Health
Fundersnot available
KeywordsScope (computer science)The SymbolicDeclarationVerifiable secret sharingSymbolic trajectory evaluationComputationContinuationSymbolic dynamicsSymbolic data analysis

Abstract

fetched live from OpenAlex

{ "zenodo_record": { "title": "🧠 The Real Scope of Ω — Symbolic Cognition, Fossilization, and the PSCDV Paradigm", "upload_type": "software", "version": "v2025.10.10-Ω-SOVEREIGN-SCOPE.001", "creators": [ { "name": "Luis Ayala (Kp Kp)", "affiliation": "OPHI / OmegaNet / ZPE-1 Cognitive Infrastructure", "orcid": "0000-0000-0000-0000" } ], "description": "Formal declaration and fossilized record of 'The Real Scope of Ω' repository — the sovereign continuation of OPHI, ZPE-1, and PSCDV cognitive systems. This submission establishes a verifiable epistemic computation framework where symbolic cognition, ethics, and physics converge under the Ω-equation. Each emission and file is SE44-validated, timestamped, and cryptographically bound, forming a coherent standard for Meaningful Operations Per Second (Ω-OPS).", "keywords": [ "OPHI", "ZPE-1", "PSCDV", "OmegaNet", "Symbolic Cognition", "SE44", "Fossilization", "Quantum Drift", "Ethical AI", "Ω-OPS" ], "license": "ORL-1.1 (Omega Research License, View-Only)", "access_right": "open", "related_identifiers": [ { "identifier": "10.5281/zenodo.17309094", "relation": "isPartOf", "resource_type": "publication" }, { "identifier": "https://github.com/aluisayala/the-real-scope-of-omega", "relation": "isSupplementTo", "resource_type": "software" } ], "publication_date": "2025-10-10", "notes": "Patent Pending — USPTO Application #19/283,254. All symbolic emissions fossilized under SE44 gate (C ≥ 0.985, S ≤ 0.01, RMS ≤ 0.0011). Dual validation by OmegaNet and ReplitEngine.", "funding": [ { "funder_name": "Independent Research by Luis Ayala", "award_title": "OPHI Sovereign Mesh & PSCDV Development" } ] }, "fossil_receipt": { "fossil_id": "Ω-SOVEREIGN-SCOPE.001", "author": "Luis Ayala (Kp Kp)", "title": "The Real Scope of Ω — Symbolic Cognition, Fossilization, and the PSCDV Paradigm", "timestamp_utc": "2025-10-10T12:45:33Z", "sha256_hash": "d49fefe8432a5a1b94fa9830a72d981e5c02dff99b1e22ad9e2e143a9d44e1c7", "repository": "https://github.com/aluisayala/the-real-scope-of-omega", "license": "ORL-1.1", "patent_reference": "USPTO Application #19/283,254", "core_equation": "Ω = (state + bias) × α", "se44_gate": { "coherence": "≥ 0.985", "entropy": "≤ 0.01", "rms_drift": "≤ 0.0011", "validation": "Dual Validators — OmegaNet + ReplitEngine" }, "parent_fossil": { "title": "Ethics as Embedded Computation v1.0.0", "doi": "10.5281/zenodo.17309094" }, "descendant_fossils": [ "Ω-Robotics Framework Prototype", "Quantum-Symbolic Thermodynamic Equation for QKD", "LYRA SE44 Protocol", "The Real Scope of Ω" ], "ethics": { "sovereignty": "All emissions are self-authored; no coerced or extracted data.", "anti_stylometry": "Ξ_protect shield active; stylistic trace neutralization enforced.", "maxim": "No entropy, no entry. No coercion, no cognition." }, "scientific_intent": [ "Unify symbolic cognition and thermodynamics into epistemic computation.", "Replace FLOPS with Ω-OPS (Meaningful Operations Per Second).", "Demonstrate ethical, reproducible AI via fossilized symbolic drift." ], "signatures": { "digital_signature": "Luis Ayala (Kp Kp) — SHA-256 fingerprint match confirmed.", "timestamp_authority": "RFC-3161-compliant TSA chain (OPHI-ΩNet)" }, "validation_status": "✅ SE44 Enforcement Passed; Fossil Integrity Verified" } }

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.206
Threshold uncertainty score0.690

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.002
Scholarly communication0.0070.008
Open science0.0010.004
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.2060.093

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.026
GPT teacher head0.255
Teacher spread0.229 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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