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Discrepancies between Predicted and Observed Intergalactic Magnetic Field Strengths from the Universe’s Total Energy: Is it Contained within Submatter Spatial Geometry?

2014· article· en· W2148024960 on OpenAlexaff
Michael A. Persinger

Bibliographic record

VenueInternational Letters of Chemistry Physics and Astronomy · 2014
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAstrophysics and Cosmic Phenomena
Canadian institutionsLaurentian University
Fundersnot available
KeywordsPhysicsParticle horizonUniverseAstrophysicsZero-energy universeGeometryMetric expansion of spaceComputational physicsDark energyCosmologyMathematics

Abstract

fetched live from OpenAlex

Although the gravitational energy within the distance of the radius of a singularity for a current estimated mass of the universe is equal to ~10 69 Joules, congruent solutions for different ages of the universe reflect changes by a factor of π or 8π for identities. The total energy value is equal to the product of primary constants G·μ·ε·ħ·σ·c 2 (which results in power, W) when divided by the area of smallest unit of space (area of a circle with a radius of Planck’s Length) and then multiplied by the universe’s current surface area and age. The conspicuous discrepancies of ~2∙10 3 between the predicted average magnetic intensity within the universe from that total energy and contemporary measurements can be accommodated by the quantitative product of 21.3π 4 derived from the classic four-dimensional metric. The equivalent electric field potential divided by the predicted magnetic intensity results in a velocity that has been suggested to reflect the latency for excess correlations to occur across the universe. The most parsimonious explanation for these results is that a large component of the magnetic manifestation of energy in the universe is recondite or occluded within its submatter spatial structure and that the required cohesion or “diffusivity” throughout the volume involves the electric field component. These quantifications may facilitate understanding of Mach’s principle that any part of the universe is influenced by all of its parts.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.394
Threshold uncertainty score0.777

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 head0.186
Teacher spread0.181 · 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 designObservational
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

Citations10
Published2014
Admission routes1
Has abstractyes

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