Power-law entropy-corrected new holographic dark energy in Brans–Dicke cosmology
Bibliographic record
Abstract
The purpose of this paper is to study power-law entropy-corrected holographic dark energy (PLECHDE) in the framework of Brans–Dicke cosmology with Granda–Oliveros (G-O) IR-cutoff. Considering the interacting and non-interacting scenario of PLECHDE with dark matter, we investigate the cosmological implications of this model in detail. We obtain the equation of state parameter, deceleration parameter, and evolution of dark energy density to explain expansion of the universe. We also determine these parameters for Ricci scale. We extend our study of the power-law entropy-corrected agegraphic dark energy model and calculate some cosmological parameters. Further, we show that the results that we calculate have good compatibility with previous work and matches it in the limiting case. Finally, we find a cosmological application of our work by evaluating the equation of state of dark energy for low red-shift.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".