The Intermediate‐Scale Clustering of Luminous Red Galaxies
Bibliographic record
Abstract
We report the intermediate-scale (0.3-40 h -1 Mpc) clustering of 35,000 luminous early-type galaxies at redshifts 0.16-0.44 from the Sloan Digital Sky Survey. We present the redshift space two-point correlation function ξ( s ), the projected correlation function w p ( r p ), and the deprojected real space correlation function ξ( r ), for approximately volume-limited samples. As expected, the galaxies are highly clustered, with the correlation length varying from 9.8 ± 0.2 to 11.2 ± 0.2 h -1 Mpc, dependent on the specific luminosity range. For the -23.2 < M g < -21.2 sample, the inferred bias relative to that of L * galaxies is 1.84 ± 0.11 for 1 h -1 Mpc < r p ≲ 10 h -1 Mpc, with yet stronger clustering on smaller scales. We detect luminosity-dependent bias within the sample but see no evidence for redshift evolution between z = 0.2 and z = 0.4. We find a clear indication for deviations from a power-law in the real space correlation function, with a dip at ~2 h -1 Mpc scales and an upturn on smaller scales. The precision measurements of these clustering trends offer new avenues for the study of the formation and evolution of these massive galaxies.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.000 |
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".