The completed SDSS-IV extended Baryon Oscillation Spectroscopic Survey: GLAM-QPM mock galaxy catalogues for the emission line galaxy sample
Bibliographic record
Abstract
ABSTRACT We present 2000 mock galaxy catalogues for the analysis of baryon acoustic oscillations (BAOs) in the Emission Line Galaxy (ELG) sample of the extended Baryon Oscillation Spectroscopic Survey Data Release 16 (eBOSS DR16). Each mock catalogue has a number density of $6.7 \times 10^{-4} h^3 \rm Mpc^{-3}$, covering a redshift range from 0.6 to 1.1. The mocks are calibrated to small-scale eBOSS ELG clustering measurements at scales of $\lesssim 30\, h^{-1}$Mpc. The mock catalogues are generated using a combination of GaLAxy Mocks (GLAM) simulations and the quick particle-mesh (QPM) method. GLAM simulations are used to generate the density field, which is then assigned dark matter haloes using the QPM method. Haloes are populated with galaxies using a halo occupation distribution. The resulting mocks match the survey geometry and selection function of the data, and have slightly higher number density that allows room for systematic analysis. The large-scale clustering of mocks at the BAO scale is consistent with data and we present the correlation matrix of the mocks.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 0.005 |
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".