The Local Cluster Survey. I. Evidence of Outside-in Quenching in Dense Environments
Bibliographic record
Abstract
Abstract The goal of the Local Cluster Survey is to look for evidence of environmentally driven quenching among star-forming galaxies in nearby galaxy groups and clusters. Quenching is linked with environment and stellar mass, and much of the current observational evidence comes from the integrated properties of galaxies. However, the relative size of the stellar and star-forming disk is sensitive to environmental processing and can help identify the mechanisms that lead to a large fraction of quenched galaxies in dense environments. Toward this end, we measure the size of the star-forming disks for 224 galaxies in nine groups and clusters (0.02 < z < 0.04; SFR > 0.1 M ⊙ yr−1) using 24 μm imaging from the Spitzer Space Telescope. We normalize the 24 μm effective radius (R 24) by the size of the stellar disk (R d ). We find that star-forming galaxies with higher bulge-to-total ratios (B/T) and galaxies in more dense environments have more centrally concentrated star formation. Comparison with H i mass fractions and NUV − r colors indicates that a galaxy’s transition from gas-rich and blue to depleted and red is accompanied by an increase in the central concentration of star formation. We build a simple model to constrain the timescale over which the star-forming disks shrink in the cluster environment. Our results are consistent with a long-timescale (>2 Gyr) mechanism that produces outside-in quenching, such as the removal of the extended gas halo or weak stripping of the cold disk gas.
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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 | 0.001 | 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) | 0.002 | 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".