Testing a varying-Λ model for dark energy within co-varying physical couplings framework
Bibliographic record
Abstract
ABSTRACT The Co-varying Physical Couplings (CPC) framework is a modified gravity set up assuming Einstein Field Equations wherein the quantities {G, c, Λ} are promoted to space–time functions. Bianchi identity and the requirement of stress-energy tensor conservation entangle the possible variations of the couplings {G, c, Λ}, which are forced to co-vary as dictated by the General Constraint (GC). In this paper, we explore a cosmological model wherein G, c, and Λ are functions of the redshift respecting the GC of the CPC framework. We assume a linear parametrization of Λ in terms of the scale factor a. We use the ansatz $\dot{G}/G = \sigma \left(\dot{c}/c \right)$ with σ = constant to deduce the functional forms of c = c(z) and G = G(z). We show that this varying-{G, c, Λ} model fits SNe Ia data and H(z) data with σ = 3. The model parameters can be constrained to describe dark energy at the background level.
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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 | 0.002 | 0.003 |
| 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 | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".