An analytical late–Universe approach to the weaving of modern cosmology
Bibliographic record
Abstract
ABSTRACT Combining cosmological probes has consolidated the standard cosmological model with per cent precision, but some tensions have recently emerged when certain parameters are estimated from the local or primordial Universe. The origin of this behaviour is still under debate; however, it is crucial to study as many probes as possible to cross-check the results with independent methods and provide additional pieces of information to the cosmological puzzle. In this work, by combining several late-Universe probes (0 < z < 10), namely, Type Ia supernovae, baryon acoustic oscillations, cosmic chronometers, and gamma-ray bursts, we aim to derive cosmological constraints independently of local or early-Universe anchors. To test the standard cosmological model and its various extensions, considering an evolving dark energy equation of state and the curvature as a free parameter, we analyse each probe individually and all their possible permutations. Assuming a flat Lambda cold dark matter (ΛCDM) model, the full combination of probes provides $H_0=67.2^{+3.4}_{-3.2}$ km s−1 Mpc−1 and Ωm = 0.325 ± 0.015 [68 per cent confidence level (C.L.)]. Considering a flat wCDM model, we measure $w_0=-0.91^{+0.07}_{-0.08}$ (68 per cent C.L.), while by relaxing the flatness assumption (ΛCDM model, 95 per cent C.L.) we obtain $\Omega _k=0.125^{+0.167}_{-0.165}$. Finally, we analytically characterize the degeneracy directions and the relative orientation of the probes’ contours. By calculating the figure-of-merit, we quantify the synergies among independent methods, estimate the constraining power of each probe, and identify which provides the best contribution to the inference process. Pending the new cosmological surveys, this study confirms the exigency for new emerging probes in the landscape of modern cosmology.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.003 | 0.003 |
| 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".