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Record W1984501500 · doi:10.1109/isscaa.2006.1627620

Physical Insight of Universe Dark Energy: the Space Mission

2006· article· en· W1984501500 on OpenAlexaff
Murad Shibli

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldPhysics and Astronomy
TopicSpace Science and Extraterrestrial Life
Canadian institutionsConcordia University
Fundersnot available
KeywordsPhysicsDark energyUniverseMomentum (technical analysis)Energy–momentum relationVariable (mathematics)Classical mechanicsSpace timeMetric expansion of spaceTheoretical physicsCosmologyAstronomyMathematics

Abstract

fetched live from OpenAlex

This paper presents a physical interpretation of what is so-called universe dark energy. This interpretation is based on geometric modeling of space-time as a phase fluid and the momentum generated by the time. In this modeling the time is considered as a mechanical variable along with other variables and treated on an equal footing. Since the momentum associated with the time as a mechanical variable is equal to the negative system total energy, the coupling in the time and its momentum leads to maximum increase in the gravitational field. The amount of energy which contributes to this increase is found to be 70.7% of the total energy. Moreover, a null paraboloid is obtained and interpreted as a function of the momentum generated by time. A space robotic mission is then proposed to probe the nature of universe dark energy. Finally, simulation results are demonstrated to verify the analytical results

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)0.000
metaresearch head score (Gemma)0.000
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: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.009
GPT teacher head0.227
Teacher spread0.219 · 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

Citations4
Published2006
Admission routes1
Has abstractyes

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