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Record W2125135004 · doi:10.1093/mnras/sts089

The Sagittarius stream and halo triaxiality

2012· article· en· W2125135004 on OpenAlexafffund
Nathan Deg, Lawrence M. Widrow

Bibliographic record

VenueMonthly Notices of the Royal Astronomical Society · 2012
Typearticle
Languageen
FieldPhysics and Astronomy
TopicGalaxies: Formation, Evolution, Phenomena
Canadian institutionsQueen's University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsPhysicsHaloAstrophysicsGalactic haloDark matter haloMilky WayDark matterSagittariusAstronomyBulgeStarsGalaxy

Abstract

fetched live from OpenAlex

We present a mass model for the Milky Way, which is fitted to observations of the Sagittarius stream together with constraints derived from a wide range of photometric and kinematic data. The model comprises a Sérsic bulge, an exponential disc and an Einasto halo. Our Bayesian analysis is accomplished using an affine-invariant Markov chain Monte Carlo algorithm. We find that the best-fitting dark matter halo is triaxial with axis ratios of 3.3 ± 0.7 and 2.7 ± 0.4 and with the short axis approximately aligned with the Sun–Galactic Centre line. Our results are consistent with those presented in Law & Majewski. Such a strongly aspherical halo is disfavoured by the standard cold dark matter scenario for structure formation.

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)0.002
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.025
Threshold uncertainty score0.049

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
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 head0.008
GPT teacher head0.202
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

Citations68
Published2012
Admission routes2
Has abstractyes

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