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Record W4392822241 · doi:10.3847/1538-4357/ad4ed2

Chemical Cartography with APOGEE: Two-process Parameters and Residual Abundances for 288,789 Stars from Data Release 17

2024· preprint· en· W4392822241 on OpenAlexafffund
Tawny Sit, David H. Weinberg, A. A. Wheeler, Christian R. Hayes, Sten Hasselquist, T. Masseron, Jennifer Sobeck

Bibliographic record

VenueThe Astrophysical Journal · 2024
Typepreprint
Languageen
FieldPhysics and Astronomy
TopicAstronomy and Astrophysical Research
Canadian institutionsHerzberg Institute of Astrophysics
FundersLawrence Berkeley National LaboratoryUniversity of Colorado BoulderOffice of ScienceMax-Planck-Institut für AstronomieMinistério da Ciência, Tecnologia e InovaçãoUniversity of OxfordYork UniversityLeibniz-GemeinschaftUniversity of Notre DameInstituto de Astrofísica de CanariasCarnegie Mellon UniversityUniversidad Nacional Autónoma de MéxicoAlfred P. Sloan FoundationUniversity of WashingtonJohns Hopkins UniversityMinisterio de Ciencia e InnovaciónCarnegie Institution of WashingtonUniversity of UtahOhio State UniversityNational Science FoundationU.S. Department of EnergySmithsonian InstitutionNew Mexico State UniversityUniversity of PortsmouthVanderbilt UniversityAgencia Estatal de InvestigaciónYale UniversityMax-Planck-Institut für Astrophysik
KeywordsStarsResidualProcess (computing)CartographyGeographyMathematicsAstrophysicsGeodesyPhysicsComputer scienceAlgorithm

Abstract

fetched live from OpenAlex

Abstract Stellar abundance measurements are subject to systematic errors that induce extra scatter and artificial correlations in elemental abundance patterns. We derive empirical calibration offsets to remove systematic trends with surface gravity <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" overflow="scroll"> <mml:mi>log</mml:mi> <mml:mo stretchy="false">(</mml:mo> <mml:mi>g</mml:mi> <mml:mo stretchy="false">)</mml:mo> </mml:math> in 17 elemental abundances of 288,789 evolved stars from the SDSS APOGEE survey. We fit these corrected abundances as the sum of a prompt process tracing core-collapse supernovae and a delayed process tracing Type Ia supernovae, thus recasting each star’s measurements into the amplitudes A cc and A Ia and the element-by-element residuals from this two-parameter fit. As a first application of this catalog, which is 8× larger than that of previous analyses that used a restricted <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" overflow="scroll"> <mml:mi>log</mml:mi> <mml:mo stretchy="false">(</mml:mo> <mml:mi>g</mml:mi> <mml:mo stretchy="false">)</mml:mo> </mml:math> range, we examine the median residual abundances of 14 open clusters, nine globular clusters, and four dwarf satellite galaxies. Relative to field Milky Way disk stars, the open clusters younger than 2 Gyr show ≈0.1−0.2 dex enhancements of the neutron-capture element Ce, and the two clusters younger than 0.5 Gyr also show elevated levels of C+N, Na, S, and Cu. Globular clusters show elevated median abundances of C+N, Na, Al, and Ce, and correlated abundance residuals that follow previously known trends. The four dwarf satellites show similar residual abundance patterns despite their different star formation histories, with ≈0.2–0.3 dex depletions in C+N, Na, and Al and ≈0.1 dex depletions in Ni, V, Mn, and Co. We provide our catalog of corrected APOGEE abundances, two-process amplitudes, and residual abundances, which will be valuable for future studies of abundance patterns in different stellar populations and of additional enrichment processes that affect galactic chemical 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 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 categoriesMeta-epidemiology (narrow), Scholarly communication, Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.881
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0020.002
Research integrity0.0000.004
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 head0.028
GPT teacher head0.316
Teacher spread0.288 · 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 designOther design
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

Citations8
Published2024
Admission routes2
Has abstractyes

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