OBSCURED STAR FORMATION IN INTERMEDIATE-DENSITY ENVIRONMENTS: A<i>SPITZER</i>STUDY OF THE ABELL 901/902 SUPERCLUSTER
Bibliographic record
Abstract
We explore the amount of obscured star formation as a function of environment in the Abell 901/902 (A901/902) supercluster at z = 0.165 in conjunction with a field sample drawn from the A901 and CDFS fields, imaged with the Hubble Space Telescope as part of the Space Telescope A901/902 Galaxy Evolution Survey and Galaxy Evolution from Morphology and Spectral Energy Distributions (SEDs) Survey. We combine the combo -17 near-UV/optical SED with Spitzer 24 μ photometry to estimate both the unobscured and obscured star formation in galaxies with M * > 10 10 M ☉ . We find that the star formation activity in massive galaxies is suppressed in dense environments, in agreement with previous studies. Yet, nearly 40% of the star-forming (SF) galaxies have red optical colors at intermediate and high densities. These red systems are not starbursting; they have star formation rates (SFRs) per unit stellar mass similar to or lower than blue SF galaxies. More than half of the red SF galaxies have low infrared-to-ultraviolet (IR-to-UV) luminosity ratios, relatively high Sérsic indices, and they are equally abundant at all densities. They might be gradually quenching their star formation, possibly but not necessarily under the influence of gas-removing environmental processes. The other ≳40% of the red SF galaxies have high IR-to-UV luminosity ratios, indicative of high dust obscuration. They have relatively high specific SFRs and are more abundant at intermediate densities. Our results indicate that while there is an overall suppression in the SF galaxy fraction with density, the small amount of star formation surviving the cluster environment is to a large extent obscured, suggesting that environmental interactions trigger a phase of obscured star formation, before complete quenching.
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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 | 0.000 |
| 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 | 0.001 | 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".