The completed SDSS-IV extended baryon oscillation spectroscopic survey: growth rate of structure measurement from anisotropic clustering analysis in configuration space between redshift 0.6 and 1.1 for the emission-line galaxy sample
Bibliographic record
Abstract
ABSTRACT We present the anisotropic clustering of emission-line galaxies (ELGs) from the Sloan Digital Sky Survey IV (SDSS-IV) extended Baryon Oscillation Spectroscopic Survey (eBOSS) Data Release 16 (DR16). Our sample is composed of 173 736 ELGs covering an area of 1170 deg2 over the redshift range 0.6 ≤ z ≤ 1.1. We use the convolution Lagrangian perturbation theory in addition to the Gaussian streaming redshift space distortions to model the Legendre multipoles of the anisotropic correlation function. We show that the eBOSS ELG correlation function measurement is affected by the contribution of a radial integral constraint that needs to be modelled to avoid biased results. To mitigate the effect from unknown angular systematics, we adopt a modified correlation function estimator that cancels out the angular modes from the clustering. At the effective redshift, zeff = 0.85, including statistical and systematical uncertainties, we measure the linear growth rate of structure fσ8(zeff) = 0.35 ± 0.10, the Hubble distance $D_ H(z_{\rm eff})/r_{\rm drag} = 19.1^{+1.9}_{-2.1}$, and the comoving angular diameter distance DM(zeff)/rdrag = 19.9 ± 1.0. These results are in agreement with the Fourier space analysis, leading to consensus values of: fσ8(zeff) = 0.315 ± 0.095, $D_H(z_{\rm eff})/r_{\rm drag} = 19.6^{+2.2}_{-2.1}$, and DM(zeff)/rdrag = 19.5 ± 1.0, consistent with ΛCDM model predictions with Planck parameters.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".