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Record W1821783097 · doi:10.1103/physrevd.91.124027

Radiative corrections in the (varying power)-law modified gravity

2015· article· en· W1821783097 on OpenAlexaff
Fayçal Hammad

Bibliographic record

VenuePhysical review. D. Particles, fields, gravitation, and cosmology/Physical review. D, Particles, fields, gravitation, and cosmology · 2015
Typearticle
Languageen
FieldPhysics and Astronomy
TopicCosmology and Gravitation Theories
Canadian institutionsBishop's UniversityChamplain Regional College
Fundersnot available
KeywordsPhysicsScalar fieldMassless particleTheoretical physicsRadiative transferCurvatureScalar (mathematics)GravitationScalar potentialClassical mechanicsMathematical physicsQuantum mechanicsGeometryMathematics

Abstract

fetched live from OpenAlex

Although the (varying power)-law modified gravity toy model has the attractive feature of unifying the early- and late-time expansions of the Universe, thanks to the peculiar dependence of the scalar field's potential on the scalar curvature, the model still suffers from the fine-tuning problem when used to explain the actually observed Hubble parameter. Indeed, a more correct estimate of the mass of the scalar field needed to comply with actual observations gives an unnaturally small value. On the other hand, for a massless scalar field the potential would have no minimum and hence the field would always remain massless. What solves these issues are the radiative corrections that modify the field's effective potential. These corrections raise the field's effective mass, rendering the model free from fine-tuning, immune against positive fifth-force tests, and better suited to tackle the dark matter sector.

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)0.001
metaresearch head score (Gemma)0.003
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 score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0010.000
Science and technology studies0.0010.003
Scholarly communication0.0010.003
Open science0.0020.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0040.001

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 head0.026
GPT teacher head0.334
Teacher spread0.308 · 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

Citations3
Published2015
Admission routes1
Has abstractyes

Explore more

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