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Record W2014726262 · doi:10.1093/mnras/stu594

Bulge mass is king: the dominant role of the bulge in determining the fraction of passive galaxies in the Sloan Digital Sky Survey

2014· article· en· W2014726262 on OpenAlexaff
Asa F. L. Bluck, J. Trevor Mendel, Sara L. Ellison, Jorge Moreno, Luc Simard, David R. Patton, Else Starkenburg

Bibliographic record

VenueMonthly Notices of the Royal Astronomical Society · 2014
Typearticle
Languageen
FieldPhysics and Astronomy
TopicGalaxies: Formation, Evolution, Phenomena
Canadian institutionsHerzberg Institute of AstrophysicsTrent UniversityUniversity of Victoria
Fundersnot available
KeywordsBulgePhysicsAstrophysicsStellar massGalaxyHaloAstronomyStar formationGalaxy formation and evolutionSkyDisc galaxySatellite galaxyGalaxy groupBimodality

Abstract

fetched live from OpenAlex

We investigate the origin of galaxy bimodality by quantifying the relative role of intrinsic and environmental drivers to the cessation (or ‘quenching’) of star formation in over half a million local Sloan Digital Sky Survey (SDSS) galaxies. Our sample contains a wide variety of galaxies at z=0.02-0.2, with stellar masses of 8< log(M∗/M) <12, spanning the entire morphological range from pure disks to spheroids, and over four orders of magnitude in local galaxy density and halo mass. We utilise published star formation rates and add to this recent GIM2D photometric and stellar mass bulge + disk decompositions from our group. We find that the passive fraction of galaxies increases steeply with stellar mass, halo mass, and bulge mass, with a less steep dependence on local galaxy density and bulge-to-total stellar mass ratio (B/T). At fixed internal properties, we find that central and satellite galaxies have different passive fraction relationships. For centrals, we conclude that there is less variation in the passive fraction at a fixed bulge mass, than for any other variable, including total stellar mass, halo mass, and B/T. This implies that the quenching mechanism must be most tightly coupled to the bulge. We argue that radio-mode AGN feedback offers the most plausible explanation of the observed trends.

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 score0.064
Threshold uncertainty score0.453

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
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 head0.006
GPT teacher head0.193
Teacher spread0.187 · 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

Citations259
Published2014
Admission routes1
Has abstractyes

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