THE ACS FORNAX CLUSTER SURVEY. VI. THE NUCLEI OF EARLY-TYPE GALAXIES IN THE FORNAX CLUSTER
Bibliographic record
Abstract
The Advanced Camera for Surveys (ACS) Fornax Cluster Survey is a Hubble Space Telescope program to image 43 early-type galaxies in the Fornax cluster, using the F475W and F850LP bandpasses of the ACS. We employ both one-dimensional and two-dimensional techniques to characterize the properties of the stellar nuclei in these galaxies, defined as the central "luminosity excesses", relative to a Sersic model fitted to the underlying host. We find 72% ± 13% of our sample (31 galaxies) to be nucleated, with only three of the nuclei offset by more than 0 5 from their galaxy photocenter, and with the majority of nuclei having colors bluer than their hosts. The nuclei are observed to be larger, and brighter, than typical Fornax globular clusters and to follow different structural scaling relations. A comparison of our results to those from the ACS Virgo Cluster Survey reveals striking similarities in the properties of the nuclei belonging to these different environments. We briefly review a variety of proposed formation models and conclude that, for the low-mass galaxies in our sample, the most important mechanism for nucleus growth is probably infall of star clusters through dynamical friction, while for higher mass galaxies, gas accretion triggered by mergers, accretions, and tidal torques is likely to dominate, with the relative importance of these two processes varying smoothly as a function of galaxy mass. Some intermediate-mass galaxies in our sample show a complexity in their inner structure that may be the signature of the "hybrid nuclei" that arose through parallel formation channels.
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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 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.016 | 0.006 |
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".