A high occurrence of nuclear star clusters in faint Coma galaxies, and the roles of mass and environment
Bibliographic record
Abstract
We use deep high resolution \textit{HST/ACS} imaging of two fields in the core of the Coma cluster to investigate the occurrence of nuclear star clusters (NSCs) in quiescent dwarf galaxies as faint as $M_{I} = -10$ mag. We employ a hierarchical Bayesian logistic regression framework to model the faint end of the nucleation fraction ($f_{n}$) as a function of both galaxy luminosity and environment. We find that $f_n$ is remarkably high in Coma: at $M_{I} \approx -13$ mag half of the cluster dwarfs still host prominent NSCs. Comparison with dwarf systems in nearby clusters and groups shows that, within the uncertainties, the rate at which the probability of nucleation varies with galaxy luminosity is nearly universal. On the other hand, the fraction of nucleated galaxies at fixed luminosity does exhibit an environmental dependence. More massive environments feature higher nucleation fractions and fainter values of the half-nucleation luminosity, which roughly scales with host halo virial mass as $L_{I,f_{n50}} \propto \mathcal{M}_{200}^{-0.2}$. Our results reinforce the role of galaxy luminosity/mass as a major driver of the efficiency of NSC formation and also indicate a clear secondary dependence on the environment, hence paving the way to more refined theoretical models.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.010 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".