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Record W4283734695 · doi:10.3847/1538-3881/ac7ce5

The Open Cluster Chemical Abundances and Mapping Survey. VI. Galactic Chemical Gradient Analysis from APOGEE DR17

2022· article· en· W4283734695 on OpenAlexfundno aff
Natalie Myers, John Donor, Taylor Spoo, Peter M. Frinchaboy, Kátia Cunha, Adrian M. Price-Whelan, Steven R. Majewski, Rachael L. Beaton, Gail Zasowski, Julia O’Connell, Amy E. Ray, Dmitry Bizyaev, C. Chiappini, D. A. García–Hernández, D. Geisler, Henrik Jönsson, Richard R. Lane, Penélope Longa-Peña, Ivan Minchev, D. Minniti, Christian Nıtschelm, Alexandre Roman–Lopes

Bibliographic record

VenueThe Astronomical Journal · 2022
Typearticle
Languageen
FieldPhysics and Astronomy
TopicStellar, planetary, and galactic studies
Canadian institutionsnot available
FundersLawrence Berkeley National LaboratoryFondo Nacional de Desarrollo Científico y TecnológicoComisión Nacional de Investigación Científica y TecnológicaUniversity of Colorado BoulderInstituto de Astrofísica de CanariasOffice of ScienceMax-Planck-Institut für AstronomieMax-Planck-Institut für AstrophysikAgencia Nacional de Investigación y DesarrolloUniversidad Nacional Autónoma de MéxicoMinistério da Ciência, Tecnologia e InovaçãoNew Mexico State UniversityCrafoordska StiftelsenUniversity of OxfordYork UniversityCarnegie Institution for ScienceMinisterio de Ciencia, Innovación y UniversidadesLeibniz-GemeinschaftUniversity of Notre DameEuropean Regional Development FundCarnegie Mellon UniversityAlfred P. Sloan FoundationUniversity of WashingtonEuropean Space AgencyJohns Hopkins UniversityCarnegie Institution of WashingtonUniversity of UtahAspen Center for PhysicsStiftelsen Olle Engkvist ByggmästareOhio State UniversityNational Science FoundationU.S. Department of EnergySmithsonian InstitutionUniversity of PortsmouthVanderbilt UniversityAgencia Estatal de InvestigaciónYale University
KeywordsOpen clusterAstrophysicsPhysicsStarsAbundance (ecology)Cluster (spacecraft)RADIUSGalactic CenterBiologyEcology

Abstract

fetched live from OpenAlex

Abstract The goal of the Open Cluster Chemical Abundances and Mapping (OCCAM) survey is to constrain key Galactic dynamic and chemical evolution parameters by the construction and analysis of a large, comprehensive, uniform data set of infrared spectra for stars in hundreds of open clusters. This sixth contribution from the OCCAM survey presents analysis of SDSS/APOGEE Data Release 17 (DR17) results for a sample of stars in 150 open clusters, 94 of which we designate to be “high-quality” based on the appearance of their color–magnitude diagram. We find the APOGEE DR17-derived [Fe/H] values to be in good agreement with those from previous high-resolution spectroscopic open cluster abundance studies. Using a subset of the high-quality sample, the Galactic abundance gradients were measured for 16 chemical elements, including [Fe/H], for both Galactocentric radius ( R GC ) and guiding center radius ( R guide ). We find an overall Galactic [Fe/H] versus R GC gradient of −0.073 ± 0.002 dex kpc −1 over the range of 6 > R GC < 11.5 kpc, and a similar gradient is found for [Fe/H] versus R guide . Significant Galactic abundance gradients are also noted for O, Mg, S, Ca, Mn, Na, Al, K, and Ce. Our large sample additionally allows us to explore the evolution of the gradients in four age bins for the remaining 15 elements.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
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 score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.019
GPT teacher head0.240
Teacher spread0.221 · 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.

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

Citations68
Published2022
Admission routes1
Has abstractyes

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