The clustering of galaxies in the SDSS-III Baryon Oscillation Spectroscopic Survey: the low-redshift sample
Bibliographic record
Abstract
We report on the small-scale (0.5 < r < 40 h−1 Mpc) clustering of 78 895 massive (M* ∼ 1011.3 M⊙) galaxies at 0.2 < z < 0.4 from the first two years of data from the Baryon Oscillation Spectroscopic Survey (BOSS), to be released as part of Sloan Digital Sky Survey (SDSS) Data Release 9 (DR9). We describe the sample selection, basic properties of the galaxies and caveats for working with the data. We calculate the real- and redshift-space two-point correlation functions of these galaxies, fit these measurements using halo occupation distribution (HOD) modelling within dark matter cosmological simulations, and estimate the errors using mock catalogues. These galaxies lie in massive haloes, with a mean halo mass of 5.2 × 1013 h−1 M⊙, a large-scale bias of ∼2.0 and a satellite fraction of 12 ± 2 per cent. Thus, these galaxies occupy haloes with average masses in between those of the higher redshift BOSS CMASS sample and the original SDSS I/II luminous red galaxy sample.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".