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Record W2374223588 · doi:10.1093/mnrasl/slw093

Probing the early chemical evolution of the Sculptor dSph with purely old stellar tracers

2016· article· en· W2374223588 on OpenAlexaff
C. E. Martínez-Vázquez, M. Monelli, Carme Gallart, G. Bono, Edouard J. Bernard, P. B. Stetson, I. Ferraro, A. R. Walker, M. Dall’Ora, G. Fiorentino, G. Iannicola

Bibliographic record

VenueMonthly Notices of the Royal Astronomical Society Letters · 2016
Typearticle
Languageen
FieldPhysics and Astronomy
TopicStellar, planetary, and galactic studies
Canadian institutionsNational Research Council CanadaHerzberg Institute of Astrophysics
FundersMinisterio de Economía y CompetitividadCentre National d’Etudes Spatiales
KeywordsMetallicityPhysicsAstrophysicsStarsGalaxyLuminosityRR Lyrae variableRed-giant branchRADIUSStellar populationAstronomyLocal GroupPopulationDwarf galaxyStar formationGlobular cluster

Abstract

fetched live from OpenAlex

Abstract We present the metallicity distribution of a sample of 471 RR Lyrae (RRL) stars in the Sculptor dSph, obtained from the I-band period–luminosity relation. It is the first time that the early chemical evolution of a dwarf galaxy is characterized in such a detailed and quantitative way, using photometric data alone. We find a broad metallicity distribution (full width at half-maximum equals to 0.8 dex) that is peaked at [Fe/H] ≃ −1.90 dex, in excellent agreement with literature values obtained from spectroscopic data. Moreover, we are able to directly trace the metallicity gradient out to a radius of ∼55 arcmin. We find that in the outer regions (r > ∼32 arcmin) the slope of the metallicity gradient from the RRLs (−0.025 dex arcmin−1) is comparable to the literature values based on red giant (RG) stars. However, in the central part of Sculptor, we do not observe the latter gradients. This suggests that there is a more metal-rich and/or younger population in Sculptor that does not produce RRLs. This scenario is strengthened by the observation of a metal-rich peak in the metallicity distribution of RG stars by other authors, which is not present in the metallicity distribution of the RRLs within the same central area.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.382

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.005
GPT teacher head0.169
Teacher spread0.164 · 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 teacher head, 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

Citations44
Published2016
Admission routes1
Has abstractyes

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