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Record W2143782024 · doi:10.1086/520843

Self‐Consistent Massive Disks in Triaxial Dark Matter Halos

2007· article· en· W2143782024 on OpenAlexaff
Jeremy Bailin, Joshua D. Simon, Alberto D. Bolatto, B. K. Gibson, Chris Power

Bibliographic record

VenueThe Astrophysical Journal · 2007
Typearticle
Languageen
FieldPhysics and Astronomy
TopicGalaxies: Formation, Evolution, Phenomena
Canadian institutionsMcMaster University
Fundersnot available
KeywordsHaloCuspy halo problemPhysicsAstrophysicsDark matter haloDark matterGalaxy rotation curveSurface brightnessGalactic haloThick diskGalaxyAstronomy

Abstract

fetched live from OpenAlex

Galactic disks in triaxial dark matter halos become deformed by the elliptical potential in the plane of the disk in such a way as to counteract the halo ellipticity. We develop a technique to calculate the equilibrium configuration of such a disk in the combined disk-halo potential, which is based on the method of Jog but accounts for the radial variation in both the halo potential and the disk ellipticity. This crucial ingredient results in qualitatively different behavior of the disk: the disk circularizes the potential at small radii, even for a reasonably low disk mass. This effect has important implications for proposals to reconcile cuspy halo density profiles with low surface brightness galaxy rotation curves using halo triaxiality. The disk ellipticities in our models are consistent with observational estimates based on two-dimensional velocity fields and isophotal axis ratios.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0020.002
Research integrity0.0010.000
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 head0.008
GPT teacher head0.221
Teacher spread0.213 · 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 designSimulation or modeling
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

Citations28
Published2007
Admission routes1
Has abstractyes

Explore more

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