A reconstruction of modified holographic Ricci dark energy in <i>f</i>(<i>R</i>, <i>T</i>) gravity
Bibliographic record
Abstract
In this paper, we consider a recently proposed model of dark energy (DE) know as modified holographic Ricci DE (which is function of the Hubble parameter and its first derivative with respect to cosmic time, t) in light of the f(R, T) model of modified gravity, considering the particular model f(R, T) = μR + νT, with μ and ν constants. The equation of state parameter ωΛ approaches but never reaches the value −1, implying a quintessence-like behavior of the model. The deceleration parameter q passes from decelerated to accelerated phase at a redshift of z ≈ 0.2, showing also a small dependence from the values of the parameters considered. Thanks to the statefinder diagnostic analysis, we observed that the ΛCDM phase for the considered model is attainable. We observed that the fractional energy densities for DE and dark matter, ΩΛ and Ωm, have an increasing and a decreasing pattern, respectively, with the evolution of the universe, indicating an evolution from matter to DE dominated universe. Finally, studying the squared speed of the sound [Formula: see text] for our model, we found that it is classically stable.
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 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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".