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Record W3163618771 · doi:10.1139/cjp-2020-0605

The scalar field models of Tsallis holographic dark energy with Granda–Oliveros cutoff in modified gravity

2021· article· en· W3163618771 on OpenAlexvenueno aff
Anirudh Pradhan, Gunjan Varshney, Umesh Kumar Sharma

Bibliographic record

VenueCanadian Journal of Physics · 2021
Typearticle
Languageen
FieldPhysics and Astronomy
TopicCosmology and Gravitation Theories
Canadian institutionsnot available
Fundersnot available
KeywordsPhysicsQuintessenceDark energyTachyonFriedmann–Lemaître–Robertson–Walker metricScalar fieldMathematical physicsCutoffDeceleration parameterUniverseScalar (mathematics)Theoretical physicsClassical mechanicsCosmologyAstrophysicsQuantum mechanicsGeometry

Abstract

fetched live from OpenAlex

This research explores the Tsallis holographic quintessence, k-essence, and tachyon models of dark energy in the modified f(R, T) gravity framework with Granda–Oliveros cutoff. We have analyzed the energy density through [Formula: see text]. We study the correspondence between the quintessence, k-essence, and tachyon energy density with the Tsallis holographic dark energy density in a flat FRW Universe. The reconstruction is performed for different values of Tsallis parameter δ in the region of ωΛ > –1 for the EoS parameter. This correspondence allows reconstruction of the potentials and the dynamics for the scalar field models, if we set some constraints for the model parameters, which describe the accelerated expansion of the Universe.

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: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.008
GPT teacher head0.205
Teacher spread0.197 · 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

Citations8
Published2021
Admission routes1
Has abstractyes

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