Globular cluster systems of early-type galaxies in low-density environments★
Bibliographic record
Abstract
Deep images of 10 early-type galaxies in low-density environments have been obtained with the Advanced Camera for Surveys (ACS) aboard the Hubble Space Telescope. The global properties of the globular cluster (GC) systems of the galaxies have been derived in order to investigate the role of the environment in galaxy formation and evolution. Using the ACS Virgo Cluster Survey as a high-density counterpart, the similarities and differences between the GC properties in high- and low-density environments are presented. We find a strong correlation of the GC mean colours and the degree of colour bimodality with the host galaxy luminosity in low-density environments, in good agreement with high-density environments. In contrast, the GC mean colours at a given host luminosity are somewhat bluer [Δ(g−z) ∼ 0.05] than those for cluster galaxies, indicating more metal poor (Δ[Fe/H] ∼ 0.10 − 0.15) and/or younger (Δage > 2 Gyr) GC systems than those in dense environments. Furthermore, with decreasing host luminosity, the colour bimodality disappears faster, when compared to galaxies in cluster environments. Our results suggest that: (1) in both high- and low-density environments, the mass of the host galaxy has the dominant effect on GC system properties; (2) the local environment has only a secondary effect on the history of GC system formation; and (3) GC formation must be governed by common physical processes across a range of environments.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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".