Galaxy assembly bias on the red sequence
Bibliographic record
Abstract
Using samples drawn from the Sloan Digital Sky Survey, we study the relationship between local galaxy density and the properties of galaxies on the red sequence. After removing the mean dependence of average overdensity (or ‘environment’) on colour and luminosity, we find that there remains a strong residual trend between luminosity-weighted mean stellar age and environment, such that galaxies with older stellar populations favour regions of higher overdensity relative to galaxies of like colour and luminosity (and hence of like stellar mass). Even when excluding galaxies with recent star formation activity (i.e. younger mean stellar ages) from the sample, we still find a highly significant correlation between stellar age and environment at fixed stellar mass. This residual age–density relation provides direct evidence for an assembly bias on the red sequence such that galaxies in higher density regions formed earlier than galaxies of similar mass in lower density environments. We discuss these results in the context of the age–metallicity degeneracy and in comparison to previous studies at low and intermediate redshift. Finally, we consider the potential role of assembly bias in explaining recent results regarding the evolution of post-starburst (or post-quenching) galaxies and the environmental dependence of the Type Ia supernova rate.
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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 | 0.002 | 0.005 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".