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Record W2768622266 · doi:10.1093/mnras/stx3001

The globular cluster NGC 7492 and the Sagittarius tidal stream: together but unmixed

2017· article· en· W2768622266 on OpenAlexaff
J. A. Carballo-Bello, J. M. Corral-Santana, M. Catelan, David Martínez‐Delgado, Ricardo R. Muñoz, A. Sollima, Camila Navarrete, S. Duffau, Patrick Côté, Marcelo D. Mora

Bibliographic record

VenueMonthly Notices of the Royal Astronomical Society · 2017
Typearticle
Languageen
FieldPhysics and Astronomy
TopicStellar, planetary, and galactic studies
Canadian institutionsHerzberg Institute of Astrophysics
FundersComisión Nacional de Investigación Científica y Tecnológica
KeywordsPhysicsGlobular clusterSagittariusAstrophysicsAstronomyCluster (spacecraft)Open clusterStar clusterStarsDwarf galaxy

Abstract

fetched live from OpenAlex

We have derived from VIMOS spectroscopy the radial velocities for a sample of 71 stars selected from CFHT/Megacam photometry around the Galactic globular cluster NGC 7492. In the resulting velocity distribution, it is possible to distinguish two relevant non-Galactic kinematic components along the same line of sight: a group of stars at 〈vr〉 ∼ 125 km s−1 which is compatible with the velocity of the old leading arm of the Sagittarius tidal stream, and a larger number of objects at 〈vr〉 ∼ −110 km s−1 that might be identified as members of the trailing wrap of the same stream. The systemic velocity of NGC 7492 set at vr ∼ −177 km s−1 differs significantly from that of both components, thus our results confirm that this cluster is not one of the globular clusters deposited by the Sagittarius dwarf spheroidal in the Galactic halo, even if it is immersed in the stream. A group of stars with 〈vr〉 ∼ − 180 km s−1 might be comprised of cluster members along one of the tidal tails of NGC 7492.

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 score0.025
Threshold uncertainty score0.049

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
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 head0.007
GPT teacher head0.207
Teacher spread0.199 · 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

Citations7
Published2017
Admission routes1
Has abstractyes

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