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Record W3130995201 · doi:10.1093/mnras/stab565

MUSE narrow field mode observations of the central kinematics of M15

2021· article· en· W3130995201 on OpenAlexafffund
Christopher Usher, Sebastian Kamann, Mark Gieles, V. Hénault-Brunet, E. Dalessandro, E. Balbinot, A. Sollima

Bibliographic record

VenueMonthly Notices of the Royal Astronomical Society · 2021
Typearticle
Languageen
FieldPhysics and Astronomy
TopicStellar, planetary, and galactic studies
Canadian institutionsSaint Mary's University
FundersH2020 European Research CouncilScience and Technology Facilities CouncilNatural Sciences and Engineering Research Council of CanadaMinisterio de Ciencia e InnovaciónVetenskapsrådet
KeywordsPhysicsKinematicsGlobular clusterIntegral field spectrographSpectrographAstrophysicsStellar kinematicsStarsRotation (mathematics)Offset (computer science)TelescopeField of viewAdaptive opticsAstronomyOpticsSpectral lineGeometryClassical mechanics

Abstract

fetched live from OpenAlex

ABSTRACT We present observations of the stellar kinematics of the centre of the core collapsed globular cluster M15 obtained with the MUSE integral field spectrograph on the Very Large Telescope operating in narrow field mode. Thanks to the use of adaptive optics, we obtain a spatial resolution of 0.1 arcsec and are able to reliably measure the radial velocities of 864 stars within 8 arcsec of the centre of M15, thus providing the largest sample of radial velocities ever obtained for the innermost regions of this system. Combined with previous observations of M15 using MUSE in wide field mode and literature data, we find that the central kinematics of M15 are complex with the rotation axis of the core of M15 offset from the rotation axis of the bulk of the cluster. While this complexity has been suggested by previous work, we confirm it at higher significance and in more detail.

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)0.000
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 score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
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 head0.014
GPT teacher head0.213
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

Citations8
Published2021
Admission routes2
Has abstractyes

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