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Record W2153484234 · doi:10.1093/mnrasl/slu139

Accretion in action: phase space coherence of stellar debris and globular clusters in Andromeda's South-West Cloud

2014· article· en· W2153484234 on OpenAlexaff
Dougal Mackey, Geraint F. Lewis, Michelle Collins, N. F. Bate, Rodrigo Ibata, Nicolas F. Martin, S. C. Chapman, A. R. Conn, Pascal J. Elahi, A. M. N. Ferguson, Avon Huxor, M. J. Irwin, Alan W. McConnachie, B. McMonigal, Jorge Peñarrubia, J. Veljanoski

Bibliographic record

VenueMonthly Notices of the Royal Astronomical Society Letters · 2014
Typearticle
Languageen
FieldPhysics and Astronomy
TopicStellar, planetary, and galactic studies
Canadian institutionsHerzberg Institute of AstrophysicsDalhousie University
FundersScience and Technology Facilities Council
KeywordsPhysicsGlobular clusterAstrophysicsAndromedaAstronomyAndromeda GalaxyMilky WayGalaxyDwarf galaxyAccretion (finance)

Abstract

fetched live from OpenAlex

ABSTRACT A central tenet of the current cosmological paradigm is that galaxies grow over time through the accretion of smaller systems. Here, we present new kinematic measurements near the centre of one of the densest pronounced substructures, the South-West Cloud, in the outer halo of our nearest giant neighbour, the Andromeda galaxy. These observations reveal that the kinematic properties of this region of the South-West Cloud are consistent with those of PA-8, a globular cluster previously shown to be co-spatial with the stellar substructure. In this sense, the situation is reminiscent of the handful of globular clusters that sit near the heart of the Sagittarius dwarf galaxy, a system that is currently being accreted into the Milky Way, confirming that accretion deposits not only stars but also globular clusters into the haloes of large galaxies.

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)0.001
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
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 head0.009
GPT teacher head0.215
Teacher spread0.206 · 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

Citations22
Published2014
Admission routes1
Has abstractyes

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