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Record W2938998294 · doi:10.3847/1538-3881/ab16f2

Ultra-diffuse Galaxies at Ultraviolet Wavelengths

2019· article· en· W2938998294 on OpenAlexaff
Dennis Zaritsky, Richard L. Donnerstein, Kristine Spekkens

Bibliographic record

VenueThe Astronomical Journal · 2019
Typearticle
Languageen
FieldPhysics and Astronomy
TopicGalaxies: Formation, Evolution, Phenomena
Canadian institutionsRoyal Military College of CanadaQueen's University
Fundersnot available
KeywordsPhysicsGalaxyUltravioletAstronomyAstrophysicsWavelengthLuminous infrared galaxyOptics

Abstract

fetched live from OpenAlex

Abstract We measure near-ultraviolet (NUV) aperture magnitudes from Galaxy Evolution Explorer images for 258 ultra-diffuse galaxy (UDG) candidates drawn from the initial Systematically Measuring Ultra-Diffuse Galaxies (SMUDGes) survey of ∼300 square degrees surrounding, and including, the Coma galaxy cluster. For the vast majority, 242 of them, we present flux upper limits due either to a lack of significant flux in the aperture or confusion with other objects projected within the aperture. These limits often place interesting constraints on the UDG candidates, indicating that they are non-star-forming or quiescent. In particular, we identify field, quiescent UDG candidates, which are a challenge for formation models and are, therefore, compelling prospects for spectroscopic follow-up and distance determinations. We present far-ultraviolet (FUV) and NUV magnitudes for 16 detected UDG candidates and compare those galaxies to the local population of galaxies on color–magnitude and specific star formation rate diagrams. The NUV-detected UDG candidates form mostly an extension toward lower stellar masses of the star-forming galaxy sequence, and none of these lie within regions of high local galaxy density. UDG candidates span a range of properties, although almost all are consistent with being quiescent, low surface brightness galaxies, regardless of environment.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.006
GPT teacher head0.200
Teacher spread0.194 · 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 source (direct Gemma or distilled Codex), 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

Citations8
Published2019
Admission routes1
Has abstractyes

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