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Record W2525797031 · doi:10.1051/0004-6361/201629787

The rotation-metallicity relation for the Galactic disk as measured in the<i>Gaia</i>DR1 TGAS and APOGEE data

2016· article· en· W2525797031 on OpenAlexfundno aff

Bibliographic record

VenueAstronomy and Astrophysics · 2016
Typearticle
Languageen
FieldPhysics and Astronomy
TopicStellar, planetary, and galactic studies
Canadian institutionsnot available
FundersLawrence Berkeley National LaboratorySmithsonian Astrophysical ObservatoryScience and Technology Facilities CouncilUniversity of Colorado BoulderInstituto de Astrofísica de CanariasOffice of ScienceMax-Planck-Institut für AstronomieMinistério da Ciência, Tecnologia e InovaçãoUniversity of OxfordYork UniversityCarnegie Institution for ScienceLeibniz-GemeinschaftUniversity of Notre DameCarnegie Mellon UniversityUniversidad Nacional Autónoma de MéxicoAlfred P. Sloan FoundationUniversity of WashingtonEuropean Space AgencyJohns Hopkins UniversityCarnegie Institution of WashingtonUniversity of UtahOhio State UniversityU.S. Department of EnergySmithsonian InstitutionPartnership for Advanced Computing in Europe AISBLNew Mexico State UniversityUniversity of PortsmouthVanderbilt UniversityYale UniversityMax-Planck-Institut für Astrophysik
KeywordsDiscThin diskRelation (database)Rotation (mathematics)Thick diskSample (material)AstrometryLarge sample

Abstract

fetched live from OpenAlex

Aims. Previous studies have found that the Galactic rotation velocity-metallicity (V-[Fe/H]) relations for the thin and thick disk populations show negative and positive slopes, respectively. The first Gaia data release includes the Tycho-Gaia Astrometric Solution (TGAS) information, which we use to analyze the V-[Fe/H] relation for a strictly selected sample with high enough astrometric accuracy. We aim to present an explanation for the slopes of the V-[Fe/H] relationship.

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)0.002
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 score0.010
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.021
GPT teacher head0.237
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

Citations25
Published2016
Admission routes1
Has abstractyes

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