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Record W2023699115 · doi:10.1088/0004-6256/137/2/3314

THE GLOBULAR CLUSTER SYSTEMS IN THE COMA ELLIPTICALS. IV: WFPC2 PHOTOMETRY FOR FIVE GIANT ELLIPTICALS ,

2009· article· en· W2023699115 on OpenAlexaff
William E. Harris, J. J. Kavelaars, David A. Hanes, C. J. Pritchet, W. A. Baum

Bibliographic record

VenueThe Astronomical Journal · 2009
Typearticle
Languageen
FieldPhysics and Astronomy
TopicGalaxies: Formation, Evolution, Phenomena
Canadian institutionsUniversity of VictoriaQueen's UniversityHerzberg Institute of AstrophysicsMcMaster University
FundersEidgenössische Materialprüfungs- und Forschungsanstalt
KeywordsAstrophysicsPhysicsGlobular clusterAstronomyGalaxyComa ClusterVirgo ClusterPhotometry (optics)Velocity dispersionComa (optics)Advanced Camera for SurveysElliptical galaxyStar formationGalaxy clusterStars

Abstract

fetched live from OpenAlex

We analyze photometric data in V and I for the globular cluster (GC) systems in five of the giant ellipticals in the Coma Cluster: NGC 4874, 4881, 4889, 4926, and IC 4051. All of the raw data, from the Hubble Space Telescope WFPC2 Archive, are analyzed in a homogeneous way so that their five cluster systems can be strictly intercompared. We find that the GC luminosity functions are quite similar to one another and reinforce the common nature of the mass distribution of old, massive star clusters in gE galaxies. The GCLF turnover derived from a composite sample of more than 9,000 GCs appears at V = 27.71 ± 0.07 (MV = −7.3), and our data reach about half a magnitude fainter – 2 – than the turnover. We find that both a simple Gaussian curve and an evolved Schechter function fit the bright half of the GCLF equally well, though the Coma GCLF is broader and has a higher “cutoff mass ” (Mc ∼ 3×10 6 M⊙) than in any of the Virgo giants. These five Coma members exhibit a huge range in GC specific frequency, from a low of SN ≃ 0.7 for NGC 4881 up to ≃ 12 for IC 4051 and NGC 4874. No single formation scenario appears able to account for these differences in otherwise-similar galaxies and may

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)0.002
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 score0.331
Threshold uncertainty score0.654

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
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 head0.009
GPT teacher head0.235
Teacher spread0.227 · 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

Citations68
Published2009
Admission routes1
Has abstractyes

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