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Record W2807813916 · doi:10.3847/1538-4357/aacb81

The Globular Cluster Systems of Ultra-diffuse Galaxies in the Coma Cluster

2018· article· en· W2807813916 on OpenAlexaff

Bibliographic record

VenueThe Astrophysical Journal · 2018
Typearticle
Languageen
FieldPhysics and Astronomy
TopicGalaxies: Formation, Evolution, Phenomena
Canadian institutionsHerzberg Institute of Astrophysics
Fundersnot available
KeywordsComa ClusterGlobular clusterGalaxyStellar densityStar clusterStellar massDwarf spheroidal galaxyDwarf galaxy

Abstract

fetched live from OpenAlex

Abstract Ultra-diffuse galaxies (UDGs) are unusual galaxies with low luminosities, similar to classical dwarf galaxies, but with sizes up to ∼5 larger than expected for their mass. Some UDGs have large populations of globular clusters (GCs), something unexpected in galaxies with such low stellar density and mass. We have carried out a comprehensive study of GCs in both UDGs and classical dwarf galaxies at comparable stellar masses using Hubble Space Telescope ( HST ) observations of the Coma cluster. We present new imaging for 33 Dragonfly UDGs with the largest effective radii (>2 kpc), and additionally include 15 UDGs and 54 classical dwarf galaxies from the HST /ACS Coma Treasury Survey and the literature. Out of a total of 48 UDGs, 27 have statistically significant GC systems, and 11 have candidate nuclear star clusters. The GC specific frequency ( S N ) varies dramatically, with the mean S N being higher for UDGs than for classical dwarfs. At constant stellar mass, galaxies with larger sizes (or lower surface brightnesses) have higher S N , with the trend being stronger at higher stellar mass. At lower stellar masses, UDGs tend to have higher S N when closer to the center of the cluster, i.e., in denser environments. The fraction of UDGs with a nuclear star cluster also depends on environment, varying from ∼40% in the cluster core, where it is slightly lower than the nucleation fraction of classical dwarfs, to ≲20% in the outskirts. Collectively, we observe an unmistakable diversity in the abundance of GCs, and this may point to multiple formation routes.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.105
Threshold uncertainty score0.592

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.007
GPT teacher head0.216
Teacher spread0.208 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations127
Published2018
Admission routes1
Has abstractyes

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