The formation and evolution of Virgo cluster galaxies - I. Broad-band optical and infrared colours
Bibliographic record
Abstract
We use a combination of deep optical (gri) and near-infrared (H) photometry to study the radially resolved colours of a broad sample of 283 Virgo cluster galaxies. For most galaxy types, we find that the median g−H colour gradient is either flat (gas-poor giants and gas-rich dwarfs) or negative (i.e. colours become bluer with increasing radius; gas-poor dwarfs, spirals and gas-poor peculiars). Later-type galaxies typically exhibit more negative gradients than early types. Given the lack of a correlation between the central colours and axial ratios of Virgo spiral galaxies, we argue that dust likely plays a small role, if at all, in setting those colour gradients. We search for possible correlations between galaxy colour and photometric structure or environment and find that the Virgo galaxy colours become redder with increasing concentration, luminosity and surface brightness, while no dependence on the clustercentric radius or local galaxy density is detected (over a range of ∼2 Mpc and ∼3–16 Mpc−2, respectively). The colours of gas-rich Virgo galaxies correlate with their neutral gas deficiencies, such that these galaxies become redder with higher deficiencies, although part of this correlation is likely driven by a latent morphology–gas deficiency trend. Comparisons with stellar population models suggest that these colour gradients arise principally from variations in stellar metallicity within these galaxies, while age variations only make a significant contribution to the colour gradients of Virgo irregulars. A detailed stellar population analysis based on this material is presented in Roediger et al. (Paper II of this series).
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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 | 0.003 | 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) | 0.001 | 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".