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Record W2011424576 · doi:10.1086/377443

Oxygen Abundances in Metal‐poor Stars

2003· article· en· W2011424576 on OpenAlexaff
J. P. Fulbright, Jennifer A. Johnson

Bibliographic record

VenueThe Astrophysical Journal · 2003
Typearticle
Languageen
FieldPhysics and Astronomy
TopicStellar, planetary, and galactic studies
Canadian institutionsDominion Astrophysical ObservatoryHerzberg Institute of Astrophysics
Fundersnot available
KeywordsStarsAstrophysicsPhysicsOxygenBalmer seriesLine (geometry)ObservableForbidden mechanismAbundance (ecology)Emission spectrumAstronomySpectral line

Abstract

fetched live from OpenAlex

We present oxygen abundances derived from both the permitted and forbidden oxygen lines for 55 subgiants and giants with [Fe/H] values between -2.7 and solar with the goal of understanding the discrepancy in the derived abundances. A first attempt, using T eff values from photometric calibrations and surface gravities from luminosities obtained agreement between the indicators for turn-off stars, but the disagreement was large for evolved stars. We find that the difference in the oxygen abundances derived from the permitted and forbidden lines is most strongly affected by T eff , and we derive a new T eff scale based on forcing the two sets of lines to give the same oxygen abundances. These new parameters, however, do not agree with other observables, such as theoretical isochrones or Balmer-line profile based T eff determinations. Our analysis finds that one-dimensional, LTE analyses (with published non-LTE corrections for the permitted lines) cannot fully resolve the disagreement in the two indicators without adopting a temperature scale that is incompatible with other temperature indicators. We also find no evidence of circumstellar emission in the forbidden lines, removing such emission as a possible cause for the discrepancy.

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)0.001
metaresearch head score (Gemma)0.004
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 score0.021
Threshold uncertainty score0.071

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0210.006

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 head0.012
GPT teacher head0.228
Teacher spread0.216 · 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

Citations69
Published2003
Admission routes1
Has abstractyes

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