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Record W2975345309 · doi:10.1139/cjp-2019-0295

Dynamics of dissipative gravitational collapse with full causal approach in <i>f</i>(<i>R</i>) gravity

2019· article· en· W2975345309 on OpenAlexvenueno aff
G. Abbas, H. Nazar

Bibliographic record

VenueCanadian Journal of Physics · 2019
Typearticle
Languageen
FieldPhysics and Astronomy
TopicCosmology and Gravitation Theories
Canadian institutionsnot available
Fundersnot available
KeywordsPhysicsDissipative systemGravitational collapseClassical mechanicsGravitationTheoretical physicsMathematical physicsQuantum mechanics

Abstract

fetched live from OpenAlex

The aim of this outline is to investigate the consequences of viscous dissipative self-gravitational collapse in non-static spherically symmetric geometry by adopting a Misner–Sharp approach in the context of f(R) metric formalism. In this outline, we propose a viable f(R) model for the physical significance of a self-gravitating system. We determine the junction conditions between interior and exterior space–times. Furthermore, we extend our work for the dissipative dark source case in both forms of heat transformation and free radiation streaming. Finally, the dissipative variables such as heat flux, bulk, and shear viscosity are evaluated in the dynamical equation and then coupled with full causal transport equations in the background of the Israel–Stewart notion. The present analysis discusses the whole study of self-gravitational collapse and recognizes the form of a reduced collapse due to decreasing gravitational mass density, which depends on thermodynamical collapsing variables.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
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 head0.006
GPT teacher head0.215
Teacher spread0.209 · 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 designSimulation or modeling
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

Citations5
Published2019
Admission routes1
Has abstractyes

Explore more

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