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Record W2113441996 · doi:10.1088/0004-6256/146/5/134

THE RADIAL VELOCITY EXPERIMENT (RAVE): FOURTH DATA RELEASE

2013· article· en· W2113441996 on OpenAlexafffund
G. Kordopatis, G. Gilmore, Matthias Steinmetz, C. Boeche, G. M. Seabroke, A. Siebert, T. Zwitter, James Binney, P. de Laverny, A. Recio–Blanco, M. Williams, T. Piffl, H. Enke, S. Roêser, A. Bijaoui, Rosemary F. Ġ. Wyse, K. C. Freeman, U. Munari, I. Carrillo, Borja Anguiano, D. Burton, R. Campbell, C. J. P. Cass, Kristin Fiegert, M. Hartley, Q. A. Parker, W. Reid, Andreas Ritter, K. S. Russell, M. Stupar, F. G. Watson, O. Bienaymé, Joss Bland‐Hawthorn, Ortwin Gerhard, B. K. Gibson, E. K. Grebel, A. Helmi, Julio F. Navarro, Claudia Conrad, Benoît Famaey, Carole Faure, A. Just, Janez Kos, G. Matijevič, P. J. McMillan, Ivan Minchev, R.‐D. Scholz, Sanjib Sharma, A. Siviero, Elizabeth Wylie de Boer, M. Žerjal

Bibliographic record

VenueThe Astronomical Journal · 2013
Typearticle
Languageen
FieldPhysics and Astronomy
TopicStellar, planetary, and galactic studies
Canadian institutionsUniversity of Victoria
FundersLeibniz-GemeinschaftScience and Technology Facilities CouncilLeibniz-Institut für Astrophysik PotsdamW. M. Keck FoundationAgence Nationale de la RechercheAustralian Astronomical Optics-MacquarieDeutsche ForschungsgemeinschaftJavna Agencija za Raziskovalno Dejavnost RSMacquarie UniversityNatural Sciences and Engineering Research Council of CanadaJohns Hopkins UniversitySchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen ForschungIstituto Nazionale di AstrofisicaNational Science Foundation
KeywordsMetallicityRadial velocityStarsPhysicsPipeline (software)Surface gravityAstrophysicsComputer science

Abstract

fetched live from OpenAlex

We present the stellar atmospheric parameters (effective temperature, surface gravity, overall metallicity), radial velocities, individual abundances, and distances determined for 425,561 stars, which constitute the fourth public data release of the RAdial Velocity Experiment (RAVE). The stellar atmospheric parameters are computed using a new pipeline, based on the algorithms of MATISSE and DEGAS. The spectral degeneracies and the Two Micron All Sky Survey photometric information are now better taken into consideration, improving the parameter determination compared to the previous RAVE data releases. The individual abundances for six elements (magnesium, aluminum, silicon, titanium, iron, and nickel) are also given, based on a special-purpose pipeline that is also improved compared to that available for the RAVE DR3 and Chemical DR1 data releases. Together with photometric information and proper motions, these data can be retrieved from the RAVE collaboration Web site and the Vizier database.

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)0.003
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.020
Threshold uncertainty score0.068

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.003
Science and technology studies0.0010.000
Scholarly communication0.0020.001
Open science0.0020.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0200.026

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 head0.023
GPT teacher head0.245
Teacher spread0.222 · 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 designNot applicable
Domainnot available
GenreDataset

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

Citations388
Published2013
Admission routes2
Has abstractyes

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