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Record W2005116494 · doi:10.1088/0004-6256/148/4/69

HIghMass—HIGH H I MASS, H I-RICH GALAXIES AT<i>z</i>∼ 0 HIGH-RESOLUTION VLA IMAGING OF UGC 9037 AND UGC 12506

2014· article· en· W2005116494 on OpenAlexaff

Bibliographic record

VenueThe Astronomical Journal · 2014
Typearticle
Languageen
FieldPhysics and Astronomy
TopicGalaxies: Formation, Evolution, Phenomena
Canadian institutionsRoyal Military College of Canada
Fundersnot available
KeywordsGalaxyDark matterStar formationHaloDark matter haloStellar mass

Abstract

fetched live from OpenAlex

We present resolved HI observations of two galaxies, UGC 9037 and UGC 12506, members of a rare subset of galaxies detected by the ALFALFA extragalactic HI survey characterized by high HI mass and high gas fraction for their stellar masses. Both of these galaxies have M$_*>10^{10}$ M$_\odot$ and M$_\text{HI}>$ M$_*$, as well as typical star formation rates for their stellar masses. How can such galaxies have avoided consuming their massive gas reservoirs? From gas kinematics, stability, star formation, and dark matter distributions of the two galaxies, we infer two radically different histories. UGC 9037 has high central HI surface density ($>10$ M$_\odot$ pc$^{-2}$). Its gas at most radii appears to be marginally unstable with non-circular flows across the disk. These properties are consistent with UGC 9037 having recently acquired its gas and that it will soon undergo major star formation. UGC 12506 has low surface densities of HI, and its gas is stable over most of the disk. We predict its gas to be HI-dominated at all except the smallest radii. We claim a very high dark matter halo spin parameter for UGC 12506 ($\lambda=0.15$), suggesting that its gas is older, and has never undergone a period of star formation significant enough to consume the bulk of its gas.

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 score0.005
Threshold uncertainty score0.863

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 studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.004
GPT teacher head0.185
Teacher spread0.181 · 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

Citations22
Published2014
Admission routes1
Has abstractyes

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