The Local Cluster Survey II: disc-dominated cluster galaxies with suppressed star formation
Bibliographic record
Abstract
ABSTRACT We investigate the role of dense environments in suppressing star formation by studying $\rm \log _{10}(M_\star /M_\odot) \gt 9.7$ star-forming galaxies in nine clusters from the Local Cluster Survey (0.0137 < z < 0.0433) and a large comparison field sample drawn from the Sloan Digital Sky Survey. We compare the star formation rate (SFR) with stellar mass relation as a function of environment and morphology. After carefully controlling for mass, we find that in all environments, the degree of SFR suppression increases with increasing bulge-to-total (B/T) ratio. In addition, the SFRs of cluster and infall galaxies at a fixed mass are more suppressed than their field counterparts at all values of B/T. These results suggest a quenching mechanism that is linked to bulge growth that operates in all environments and an additional mechanism that further reduces the SFRs of galaxies in dense environments. We limit the sample to B/T ≤ 0.3 galaxies to control for the trends with morphology and find that the excess population of cluster galaxies with suppressed SFRs persists. We model the time-scale associated with the decline of SFRs in dense environments and find that the observed SFRs of the cluster core galaxies are consistent with a range of models including a mechanism that acts slowly and continuously over a long (2–5 Gyr) time-scale, and a more rapid (<1 Gyr) quenching event that occurs after a delay period of 1–6 Gyr. Quenching may therefore start immediately after galaxies enter clusters.
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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".