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Record W2136664099 · doi:10.1088/0004-637x/694/1/396

THE ROLE OF COLD FLOWS IN THE ASSEMBLY OF GALAXY DISKS

2009· article· en· W2136664099 on OpenAlexaff

Bibliographic record

VenueThe Astrophysical Journal · 2009
Typearticle
Languageen
FieldPhysics and Astronomy
TopicGalaxies: Formation, Evolution, Phenomena
Canadian institutionsMcMaster University
Fundersnot available
KeywordsAccretion (finance)GalaxyCooling flowVirial massVirial theoremHaloStar formationGalaxy formation and evolutionRADIUSRedshift

Abstract

fetched live from OpenAlex

We use high-resolution cosmological hydrodynamical simulations to demonstrate that cold flow gas accretion, particularly along filaments, modifies the standard picture of gas accretion and cooling onto galaxy disks. In the standard picture, all gas is initially heated to the virial temperature of the galaxy as it enters the virial radius. Low-mass galaxies are instead dominated by accretion of gas that stays well below the virial temperature, and even when a hot halo is able to develop in more massive galaxies there exist dense filaments that penetrate inside of the virial radius and deliver cold gas to the central galaxy. For galaxies up to ~L*, this cold accretion gas is responsible for the star formation (SF) in the disk at all times to the present. Even for galaxies at higher masses, cold flows dominate the growth of the disk at early times. Within this modified picture, galaxies are able to accrete a large mass of cold gas, with lower initial gas temperatures leading to shorter cooling times to reach the disk. Although SF in the disk is mitigated by supernovae feedback, the short cooling times allow for the growth of stellar disks at higher redshifts than predicted by the standard model.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.590
Threshold uncertainty score0.234

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.005
GPT teacher head0.213
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

Citations348
Published2009
Admission routes1
Has abstractyes

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