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Record W4312395737 · doi:10.56431/p-n490wt

Relating Casimir to Magnetic Energies Results in Spatial Dimensions that Define Biology Systems

2014· article· en· W4312395737 on OpenAlexaff
Michael A. Persinger

Bibliographic record

VenueInternational Letters of Chemistry Physics and Astronomy · 2014
Typearticle
Languageen
FieldPhysics and Astronomy
TopicQuantum Electrodynamics and Casimir Effect
Canadian institutionsLaurentian University
Fundersnot available
KeywordsPhysicsCasimir effectElectronMagnetic momentPhotonRADIUSMagnetic fieldMagnetic energyMoment (physics)WavelengthBohr radiusAtomic physicsProtonComputational physicsQuantum electrodynamicsClassical mechanicsQuantum mechanicsMagnetization

Abstract

fetched live from OpenAlex

The volume-independence that occurs when Casimir and magnetic energies were equated wasemployed to solve for optimal spatial separations. For the magnetic moments of a proton and anelectron in the presence of a magnetic field strength that produced the energy associated with theneutral hydrogen line, the distances were 1 nm and 24 nm or the width of an ion channel in a plasmacell membrane and the average synaptic width, respectively. The small discrepancies in orbit-spinmagnetic moments of the electron with the magnetic moment of the proton emerged as relevant.Calculation of the radius in the bound (circular) system associated with the required magnetic fieldstrength for the ~3.41·10 -27 A·m 2 discrepancy solved as the Compton wavelength of the electron.Applications of the approach allowed quantitative convergence between universal photon densitieswithin 1 nm widths as well as integration of the energy from acceleration for estimated upper limits ofresting photon masses with Planck’s constant. The results suggest that the physical and chemicalproperties that define biological systems, particularly the brain, reflect astronomical principles.

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 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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.201
Threshold uncertainty score0.679

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.005
GPT teacher head0.212
Teacher spread0.208 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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

Citations2
Published2014
Admission routes1
Has abstractyes

Explore more

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