Measurement of baryon acoustic oscillation correlations at<i>z</i> = 2.3 with SDSS DR12 Ly<i>α</i>-Forests
Bibliographic record
Abstract
We have used flux-transmission correlations in Lyα forests to measure the imprint of baryon acoustic oscillations (BAO). The study uses spectra of 157 783 quasars in the redshift range 2.1 ≤ z ≤ 3.5 from the Sloan Digital Sky Survey (SDSS) data release 12 (DR12). Besides the statistical improvements on our previous studies using SDSS DR9 and DR11, we have implemented numerous improvements in the analysis procedure, allowing us to construct a physical model of the correlation function and to investigate potential systematic errors in the determination of the BAO peak position. The Hubble distance, DH = c/H(z), relative to the sound horizon is DH(z = 2.33) /rd = 9.07 ± 0.31. The best-determined combination of comoving angular-diameter distance, DM, and the Hubble distance is found to be DH0.7DM0.3 /rd = 13.94 ± 0.35. This value is 1.028 ± 0.026 times the prediction of the flat-ΛCDM model consistent with the cosmic microwave background (CMB) anisotropy spectrum. The errors include marginalization over the effects of unidentified high-density absorption systems and fluctuations in ultraviolet ionizing radiation. Independently of the CMB measurements, the combination of our results and other BAO observations determine the open-ΛCDM density parameters to be ΩM = 0.296 ± 0.029, ΩΛ = 0.699 ± 0.100 and Ωk = −0.002 ± 0.119.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".