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Record W6912106994 · doi:10.5281/zenodo.15978543

When the Universe Talks to Itself: φ-Harmonic Resonance, DNA Geometry, and Instantaneous Data Transfer

2025· preprint· en· W6912106994 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2025
Typepreprint
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicFractal and DNA sequence analysis
Canadian institutionsFields Institute for Research in Mathematical Sciences
Fundersnot available
KeywordsCoherence (philosophical gambling strategy)Probabilistic logicPreprintQuantumUniverseInformation theoryCoherent informationQuantum information

Abstract

fetched live from OpenAlex

This preprint introduces a novel hypothesis connecting biological architecture and information theory through universal harmonic principles. We argue that the φ-structured geometry of DNA’s double helix reflects the same resonance framework governing matter coherence across scales, as predicted by the Resonant Order Theory of Everything (ROTE). Building on this foundation, we propose a deterministic communication model based on ψ-field phase-locking, enabling instantaneous, energy-free data transfer—surpassing the probabilistic limitations of quantum entanglement. The study presents the theoretical underpinnings, alignment of DNA geometry with φ-harmonic structures, and implications for next-generation communication systems. This work challenges prevailing assumptions in quantum information science and offers a unified view of resonance as the organizing principle of both structure and connectivity in the universe.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesOpen science, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.547
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0020.008
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.033
GPT teacher head0.251
Teacher spread0.218 · 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