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Record W2054732781 · doi:10.1086/521424

Stromgren Photometry of Galactic Globular Clusters. I. New Calibrations of the Metallicity Index

2007· article· en· W2054732781 on OpenAlexaff
A. Calamida, G. Bono, P. B. Stetson, L. M. Freyhammer, S. Cassisi, F. Grundahl, A. Pietrinferni, M. Hilker, F. Primas, T. Richtler, M. Romaniello, R. Buonanno, F. Caputo, M. Castellani, C. Corsi, I. Ferraro, G. Iannicola, L. Pulone

Bibliographic record

VenueThe Astrophysical Journal · 2007
Typearticle
Languageen
FieldPhysics and Astronomy
TopicStellar, planetary, and galactic studies
Canadian institutionsDominion Astrophysical ObservatoryHerzberg Institute of Astrophysics
Fundersnot available
KeywordsMetallicityGlobular clusterPhotometry (optics)AstrophysicsPhysicsStarsRed-giant branchAstronomy

Abstract

fetched live from OpenAlex

We present a new calibration of the Strömgren metallicity index m 1 using red giant (RG) stars in four globular clusters (GCs: M92, M13, NGC 1851, 47 Tuc) with metallicity ranging from -2.2 to -0.7, marginally affected by reddening [ E ( B - V ) ≤ 0.04] and with accurate ( u , v , b , y ) photometry. The main difference between the new metallicity-index-color (MIC) relations and similar relations available in the literature is that we have adopted the u - y and v - y colors instead of b - y . These colors present a stronger sensitivity to effective temperature, and the MIC relations show a linear slope. The difference between photometric estimates and spectroscopic measurements for RGs in M71, NGC 288, NGC 362, NGC 6397, and NGC 6752 is 0.04 ± 0.03 dex (σ = 0.11 dex). We also apply the new MIC relations to 85 field RGs with metallicity ranging from -2.4 to -0.5 and accurate reddening estimates. We find that the difference between photometric estimates and spectroscopic measurements is -0.14 ± 0.01 dex (σ = 0.17 dex). We also provide two sets of MIC relations based on evolutionary models that have been transformed into the observational plane by adopting either semiempirical or theoretical color-temperature relations. We apply the semiempirical relations to the nine GCs and find that the difference between photometric and spectroscopic metallicities is 0.04 ± 0.03 dex (σ = 0.10 dex). A similar agreement is found for the sample of field RGs, with a difference of -0.09 ± 0.03 dex (with σ = 0.19 dex). The difference between metallicity estimates based on theoretical relations and spectroscopic measurements is -0.11 ± 0.03 dex (σ = 0.14 dex) for the nine GCs and -0.24 ± 0.03 dex (σ = 0.15 dex) for the field RGs. Current evidence indicates that new MIC relations provide metallicities with an intrinsic accuracy better than 0.2 dex.

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)0.002
metaresearch head score (Gemma)0.003
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 score0.006
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.002
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0060.004

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 head0.239
Teacher spread0.227 · 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

Citations73
Published2007
Admission routes1
Has abstractyes

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