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Record W4415494005 · doi:10.5539/apr.v17n2p141

Revisiting the Universe Expansion and Dark Energy Problem

2025· article· W4415494005 on OpenAlexvenueno aff
J.G. Bartzis

Bibliographic record

VenueApplied Physics Research · 2025
Typearticle
Language
FieldPhysics and Astronomy
TopicCosmology and Gravitation Theories
Canadian institutionsnot available
Fundersnot available
KeywordsDark energyCosmological constantHubble's lawMetric expansion of spaceLambda-CDM modelPlanckVacuum energyUniverseCosmological constant problemAge of the universe

Abstract

fetched live from OpenAlex

The prevailing cosmological consensus supports an accelerating universe driven by dark energy, typically modeled as a cosmological constant. However, ongoing observational tensions—such as the Hubble constant discrepancy—and theoretical inconsistencies, including the cosmological constant problem, call for a fresh conceptual approach. This work introduces a new framework grounded in two core hypotheses: (1) that the Hubble parameter evolves inversely with the age of the universe, and (2) that dark energy dynamically balances gravitational attraction in accordance with Newton’s third law. Under this model, the universe expands at a constant rate (zero acceleration), supported by a continuous inflow of vacuum energy characterized by a universal constant energy rate (ER). The framework reproduces energy density values consistent with quantum field theory at Planck scales and offers a potential resolution to both the cosmological constant and Hubble tension problems. Further analysis shows that the energy rate (ER) can be parameterized using Planck units, naturally leading to quantized interpretations of time and energy. This supports a view of spacetime underpinned by discrete Planck-scale structures and aligns with emerging perspectives from quantum gravity. Preliminary comparisons with observational H(z) data show promising alignment, supporting further investigation into the framework's validity and implications for cosmological theory.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
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 score0.838
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.001
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.001
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 head0.023
GPT teacher head0.323
Teacher spread0.300 · 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.

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
Published2025
Admission routes1
Has abstractyes

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