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Record W1667722556 · doi:10.1088/0004-637x/808/2/148

SYSTEMATIC Non-LTE STUDY OF THE −2.6 ≤ [Fe/H] ≤ 0.2 F AND G DWARFS IN THE SOLAR NEIGHBORHOOD. I. STELLAR ATMOSPHERE PARAMETERS

2015· article· en· W1667722556 on OpenAlexaboutno aff

Bibliographic record

VenueThe Astrophysical Journal · 2015
Typearticle
Languageen
FieldPhysics and Astronomy
TopicStellar, planetary, and galactic studies
Canadian institutionsnot available
Fundersnot available
KeywordsSubgiantEffective temperatureMetallicitySurface gravityMicroturbulenceStarsStellar atmosphereSpectral lineAtmospheric modelsLine (geometry)

Abstract

fetched live from OpenAlex

We present atmospheric parameters for 51 nearby F and G dwarf and subgiant stars uniformly distributed over the metallicity range that is suitable for the Galactic chemical evolution research. Lines of iron in the two ionization stages, Fe i and Fe ii , were used to derive a homogeneous set of effective temperatures, surface gravities, iron abundances, and microturbulence velocities. Our spectroscopic analyses took advantage of employing high-resolution ( R ≥ 60,000) Shane/Hamilton and Canada–France–Hawaii Telescope/ESPaDOnS observed spectra and non-LTE (NLTE) line formation for Fe i and Fe ii in the classical one-dimensional model atmospheres. The spectroscopic method was tested in advance with the 20 benchmark stars, for which there are multiple measurements of the infrared flux method effective temperature and their Hipparcos parallax error is less than 10%. We found NLTE abundances from lines of Fe i and Fe ii to be consistent within 0.06 dex for every benchmark star, when applying a scaling factor of = 0.5 to the Drawinian rates of inelastic Fe+H collisions. The obtained atmospheric parameters were checked for each program star by comparing its position in the log g – plane with the theoretical evolutionary track of given metallicity and α -enhancement in the Yi et al. grid. Our final effective temperatures lie exactly in between the scales of Alonso et al. and Casagrande et al., with a mean difference of +46 and −51 K, respectively. NLTE leads to higher surface gravity compared with that for LTE. The shift in log g is smaller than 0.1 dex for stars with [Fe/H] , ≤ 5750 K, or log g ≥ 4.20. NLTE analysis is crucial for the very metal-poor turnoff and subgiant stars, for which the shift in log g between NLTE and LTE can be up to 0.5 dex. The obtained accurate atmospheric parameters will be used in the forthcoming papers to determine NLTE abundances of important astrophysical elements from lithium to europium and to improve observational constraints on the chemodynamical models of the Galaxy evolution.

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 score0.012
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.015
GPT teacher head0.226
Teacher spread0.211 · 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

Citations86
Published2015
Admission routes1
Has abstractyes

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