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Record W3102315866

Investigation of a sample of carbon-enhanced metal-poor stars observed with FORS and GMOS

2018· article· en· W3102315866 on OpenAlexaboutno aff

Bibliographic record

VenueMPG.PuRe (Max Planck Society) · 2018
Typearticle
Languageen
FieldPhysics and Astronomy
TopicStellar, planetary, and galactic studies
Canadian institutionsnot available
Fundersnot available
KeywordsStarsPhysicsMetallicityAstrophysicsSpectrographAbundance (ecology)Carbon starPopulationGalaxyAstronomySpectral line
DOInot available

Abstract

fetched live from OpenAlex

<BR /> Aims: Carbon-enhanced metal-poor (CEMP) stars represent a sizeable fraction of all known metal-poor stars in the Galaxy. Their formation and composition remains a significant topic of investigation within the stellar astrophysics community. <BR /> Methods: We analysed a sample of low-resolution spectra of 30 dwarf stars, obtained using the visual and near UV FOcal Reducer and low dispersion Spectrograph for the Very Large Telescope (FORS/VLT) of the European Southern Observatory (ESO) and the Gemini Multi-Object Spectrographs (GMOS) at the GEMINI telescope, to derive their metallicity and carbon abundance. <BR /> Results: We derived C and Ca from all spectra, and Fe and Ba from the majority of the stars. <BR /> Conclusions: We have extended the population statistics of CEMP stars and have confirmed that in general, stars with a high C abundance belonging to the high C band show a high Ba-content (CEMP-s or -r/s), while stars with a normal C abundance or that are C-rich, but belong to the low C band, are normal in Ba (CEMP- no). Based on observations made with ESO Telescopes at the La Silla Paranal Observatory under programme ID 099.D-0791.Based on observations obtained at the Gemini Observatory (processed using the Gemini IRAF package), which is operated by the Association of Universities for Research in Astronomy, Inc., under a cooperative agreement with the NSF on behalf of the Gemini partnership: the National Science Foundation (United States), the National Research Council (Canada), CONICYT (Chile), Ministerio de Ciencia, Tecnología e Innovación Productiva (Argentina), and Ministério da Ciência, Tecnologia e Inovação (Brazil).Tables 1 and 2 are also available at the CDS via anonymous ftp to <A href="http://cdsarc.u-strasbg.fr">http://cdsarc.u-strasbg.fr</A> (ftp://130.79.128.5) or via <A href="http://cdsarc.u-strasbg.fr/viz- bin/qcat?J/A+A/614/A68">http://cdsarc.u-strasbg.fr/viz- bin/qcat?J/A+A/614/A68</A>

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 score0.131
Threshold uncertainty score0.672

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.023
GPT teacher head0.211
Teacher spread0.188 · 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

Citations17
Published2018
Admission routes1
Has abstractyes

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