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Record W2955743021 · doi:10.3847/1538-3881/ab3cc1

Single-lined Spectroscopic Binary Star Candidates from a Combination of the RAVE and Gaia DR2 Surveys

2019· article· en· W2955743021 on OpenAlexafffund

Bibliographic record

VenueThe Astronomical Journal · 2019
Typearticle
Languageen
FieldPhysics and Astronomy
TopicStellar, planetary, and galactic studies
Canadian institutionsUniversity of Victoria
FundersLeibniz-GemeinschaftAustralian Research CouncilScience and Technology Facilities CouncilNatural Sciences and Engineering Research Council of CanadaAustralian Astronomical Optics-MacquarieDeutsche ForschungsgemeinschaftJavna Agencija za Raziskovalno Dejavnost RSMacquarie UniversityJohns Hopkins UniversityW. M. Keck FoundationAgence Nationale de la RechercheLeibniz-Institut für Astrophysik PotsdamAustralian National UniversityNational Science FoundationEuropean Space AgencySchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen ForschungIstituto Nazionale di Astrofisica
KeywordsAstrometryRadial velocityStarsOrbital elementsBinary starBinary numberSpectral lineAsymmetry

Abstract

fetched live from OpenAlex

Abstract The combination of the final version of the Radial Velocity Experiment (RAVE) spectroscopic survey data release 6 with radial velocities (RVs) and astrometry from Gaia DR2 allows us to identify and create a catalog of single-lined binary star candidates (SB1), their inferred orbital parameters, and to inspect possible double-lined binary stars (SB2). A probability function for the detection of RV variations is used for identifying SB1 candidates. The estimation of orbital parameters for main-sequence dwarfs is performed by matching the measured RVs with theoretical velocity curves sampling the orbital parameter space. The method is verified by studying a mock sample from the SB 9 catalog. Studying the boxiness and asymmetry of the spectral lines allows us to identify possible SB2 candidates, while matching their spectra to a synthetic library indicates probable properties of their components. From the RAVE catalog we select 37,664 stars with multiple RV measurements and identify 3838 stars as SB1 candidates. Joining R ave and Gaia DR2 yields 450,646 stars with RVs measured by both surveys and 27,716 of them turn out to be SB1 candidates, which is an increase by an order of magnitude over previous studies. For main-sequence dwarf candidates we calculate their most probable orbital parameters: orbital periods are not longer than a few years and primary components have masses similar to the solar mass. All our results are available in the electronic version.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.460

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.009
GPT teacher head0.207
Teacher spread0.198 · 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.

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

Citations21
Published2019
Admission routes2
Has abstractyes

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