Cosmological constraints from baryon acoustic oscillations and clustering of large-scale structure
Bibliographic record
Abstract
We constrain cosmological parameters using combined measurements of the baryon acoustic oscillation (BAO) feature in the correlation function of galaxies and Lyα absorbers that together cover 0.1 < z < 2.4. The BAO position measurements alone – without fixing the absolute sound horizon ‘standard ruler’ length with cosmic microwave background (CMB) data – constrain Ωm = 0.303 ± 0.040 (68 per cent confidence) for a flat Λ cold dark matter (ΛCDM) model, and |$w=-1.06^{+0.33}_{-0.32}$|, |$\Omega _{\rm m}=0.292^{+0.045}_{-0.040}$| for a flat wCDM model. Adding other large-scale structure (LSS) clustering constraints – correlation function shape, the Alcock–Paczynski test and growth rate information – to the BAO considerably tightens constraints (Ωm = 0.290 ± 0.019, H0 = 67.5 ± 2.8 km s−1 Mpc−1, σ8 = 0.80 ± 0.05 for ΛCDM, and w = −1.14 ± 0.19 for wCDM). The LSS data mildly prefer a lower value of H0, and a higher value of Ωm, than local distance ladder and Type IA supernovae (SNe) measurements, respectively. While tension in the combined CMB, SNe and distance ladder data appear to be relieved by allowing w < −1, this freedom introduces tension with the LSS σ8 constraint from the growth rate of matter fluctuations. The combined constraint on w from CMB, BAO and LSS clustering for a flat wCDM model is w = −1.03 ± 0.06.
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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 | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".