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Record W1771468395 · doi:10.1051/0004-6361/201423974

Chemical gradients in the Milky Way from the RAVE data

2014· article· en· W1771468395 on OpenAlexafffund
C. Boeche, A. Siebert, T. Piffl, A. Just, M. Steinmetz, E. K. Grebel, Sanjib Sharma, G. Kordopatis, G. Gilmore, C. Chiappini, K. C. Freeman, B. K. Gibson, U. Munari, A. Siviero, O. Bienaymé, Julio F. Navarro, Q. A. Parker, W. Reid, G. M. Seabroke, F. G. Watson, R. F. G. Wyse, T. Zwitter

Bibliographic record

VenueAstronomy and Astrophysics · 2014
Typearticle
Languageen
FieldPhysics and Astronomy
TopicStellar, planetary, and galactic studies
Canadian institutionsUniversity of VictoriaSaint Mary's University
FundersLeibniz-GemeinschaftAustralian Research CouncilScience and Technology Facilities CouncilAustralian Astronomical Optics-MacquarieDeutsche ForschungsgemeinschaftJavna Agencija za Raziskovalno Dejavnost RSMacquarie UniversityNatural Sciences and Engineering Research Council of CanadaJohns Hopkins UniversityW. M. Keck FoundationAgence Nationale de la RechercheAustralian National UniversitySchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen ForschungIstituto Nazionale di AstrofisicaNational Science Foundation
KeywordsMilky WayAstrophysicsPhysicsGalactic planeStarsSample (material)Plane (geometry)GeometryMathematics

Abstract

fetched live from OpenAlex

Aims. We provide new constraints on the chemo-dynamical models of the Milky Way by measuring the radial and vertical chemical gradients for the elements Mg, Al, Si, Ti, and Fe in the Galactic disc and the gradient variations as a function of the distance from the Galactic plane (Z).

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)0.001
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 score0.007
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
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 head0.015
GPT teacher head0.212
Teacher spread0.197 · 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

Citations67
Published2014
Admission routes2
Has abstractyes

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