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Record W2951904240 · doi:10.1139/cjp-2019-0135

Accelerated expansion of the Universe in the presence of dark matter pressure

2019· article· en· W2951904240 on OpenAlexvenueno aff
Zeinab Rezaei

Bibliographic record

VenueCanadian Journal of Physics · 2019
Typearticle
Languageen
FieldPhysics and Astronomy
TopicCosmology and Gravitation Theories
Canadian institutionsnot available
FundersShiraz University
KeywordsPhysicsDark energyDark fluidMetric expansion of spaceEquation of stateScale factor (cosmology)AstrophysicsBig RipDark matterDeceleration parameterCold dark matterAge of the universeScalar field dark matterUniverseHubble's lawHot dark matterRedshiftCosmologyDe Sitter universeHubble volumeGalaxyQuantum mechanics

Abstract

fetched live from OpenAlex

Expansion dynamics of the Universe is an important subject in modern cosmology. The dark energy equation of state determines these dynamics so that the Universe is in an accelerating phase. However, dark matter (DM) can also affect the accelerated expansion of the Universe through its equation of state. In the present work, we explore the expansion dynamics of the Universe in the presence of DM pressure. In this regard, applying the DM equation of state from the observational data related to the rotational curves of galaxies, we calculate the evolution of DM density. Moreover, the Hubble parameter, history of scale factor, luminosity distance, and deceleration parameter are studied while the DM pressure is taken into account. Our results verify that the DM pressure leads to higher values of the Hubble parameter at each redshift and the expansion of the Universe grows due to the DM pressure.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.217
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 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
Published2019
Admission routes1
Has abstractyes

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