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Record W1970791222 · doi:10.1086/425547

Mass Segregation and Tidal Tails of the Globular Cluster NGC 7492

2004· article· en· W1970791222 on OpenAlexaff
Kang Hwan Lee, Hyung Mok Lee, Gregory G. Fahlman, Hwankyung Sung

Bibliographic record

VenueThe Astronomical Journal · 2004
Typearticle
Languageen
FieldPhysics and Astronomy
TopicStellar, planetary, and galactic studies
Canadian institutionsHerzberg Institute of Astrophysics
Fundersnot available
KeywordsGlobular clusterAstrophysicsCluster (spacecraft)PhysicsOpen clusterGeologyStarsComputer science

Abstract

fetched live from OpenAlex

We present a wide-field CCD photometric study of the Galactic globular cluster NGC 7492. The derived VR color-magnitude diagram (CMD) extends down to about 3.5 mag below the cluster main-sequence turnoff. The field covers 42' × 42', about 3 times larger than the known tidal radius of this cluster. The sample of cluster member candidates obtained by the CMD-mask process has been used to construct luminosity (LFs) and mass functions (MFs) and a surface density map. NGC 7492 has a very flat MF with very little variation in the slope with distance from the cluster center. However, there is a clear evidence for an increase of the MF slope from inner to outer regions, indicating mass segregation of the cluster. The surface density map of NGC 7492 shows extensions toward the Galactic anticenter (northeast) and northwest from the cluster center. A comparison of the LF for stars in the tails with that for stars within the tidal radius suggests that the extensions shown in the surface density map could be a real feature. The overall shape of NGC 7492 is significantly flattened. If the flattened shape of the NGC 7492 is caused by its rotation, the Galactic tidal field must have been an important influence, since the initial rotation would have been almost completely removed by dynamical relaxation.

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 score0.012
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.006
GPT teacher head0.200
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

Citations26
Published2004
Admission routes1
Has abstractyes

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