The build-up of the colour-magnitude relation in galaxy clusters since z 0.8
Bibliographic record
Abstract
Using galaxy clusters from the ESO Distant Cluster Survey, we study how the distribution of galaxies along the colour–magnitude relation has evolved since z∼ 0.8. While red-sequence galaxies in all these clusters are well described by an old, passively evolving population, we confirm our previous finding of a significant evolution in their luminosity distribution as a function of redshift. When compared to galaxy clusters in the local Universe, the high-redshift EDisCS clusters exhibit a significant deficit of faint red galaxies. Combining clusters in three different redshift bins, and defining as ‘faint’ all galaxies in the range 0.4 ≳L/L*≳ 0.1, we find a clear decrease in the luminous-to-faint ratio of red galaxies from z∼ 0.8 to ∼0.4. The amount of such a decrease appears to be in qualitative agreement with predictions of a model where the blue bright galaxies that populate the colour–magnitude diagram of high-redshift clusters, have their star formation suppressed by the hostile cluster environment. Although model results need to be interpreted with caution, our findings clearly indicate that the red-sequence population of high-redshift clusters does not contain all progenitors of nearby red-sequence cluster galaxies. A significant fraction of these must have moved on to the red sequence below z∼ 0.8.
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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 | 0.004 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".