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Record W4303700159 · doi:10.5539/apr.v14n2p29

Characterization of Dark Energy and Derivation of Hubble’s Constant Using Harmonic Quintessence

2022· article· en· W4303700159 on OpenAlexaffvenue
Andrew Worsley, James F. Peters, Joseph Worsley

Bibliographic record

VenueApplied Physics Research · 2022
Typearticle
Languageen
FieldPhysics and Astronomy
TopicExperimental and Theoretical Physics Studies
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsQuintessenceDark energyPhysicsPlanckCosmological constantHubble's lawDark fluidQuantum electrodynamicsAstrophysicsClassical mechanicsCosmology

Abstract

fetched live from OpenAlex

In this paper, using harmonic quintessence, it is shown that the fundamental parameterization of dark energy can be determined using Planck’s constant. This allows the derivation of the mass density, and in turn we obtain the energy density of dark energy. This characterization of dark energy also allows the derivation of an averaged value of Hubble’s constant, which is in keeping with results from the Planck telescope. It is also possible to confirm the vacuum electric permittivity, magnetic permeability and the field equations for dark energy and corroborate the continued expansion of the Universe. This establishes the fundamental element of the Universe, derived from Planck’s constant, as Harmonic Quintessence.

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)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0010.002
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0040.001

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 head0.043
GPT teacher head0.318
Teacher spread0.276 · 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 designTheoretical or conceptual
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

Citations0
Published2022
Admission routes2
Has abstractyes

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