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Record W2513106860 · doi:10.1093/mnras/stw2133

Dwarf nova-type cataclysmic variable stars are significant radio emitters

2016· article· en· W2513106860 on OpenAlexafffund
D. L. Coppejans, Elmar Körding, J. C. A. Miller‐Jones, M. P. Rupen, G. R. Sivakoff, C. Knigge, P. Groot, P. A. Woudt, Elizabeth O. Waagen, Matthew R. Templeton

Bibliographic record

VenueMonthly Notices of the Royal Astronomical Society · 2016
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAstrophysical Phenomena and Observations
Canadian institutionsUniversity of AlbertaHerzberg Institute of Astrophysics
FundersScience and Technology Facilities CouncilNatural Sciences and Engineering Research Council of CanadaNederlandse Organisatie voor Wetenschappelijk OnderzoekLeverhulme TrustNational Aeronautics and Space AdministrationNational Science Foundation
KeywordsPhysicsAstrophysicsCataclysmic variable starLuminosityDwarf novaLight curveStarsAstronomyVariable starWhite dwarf

Abstract

fetched live from OpenAlex

We present 8–12 GHz radio light curves of five dwarf nova (DN) type cataclysmic variable stars (CVs) in outburst (RX And, U Gem, and Z Cam), or superoutburst (SU UMa and YZ Cnc), increasing the number of radio-detected DN by a factor of 2. The observed radio emission was variable on time-scales of minutes to days, and we argue that it is likely to be synchrotron emission. This sample shows no correlation between the radio luminosity and optical luminosity, orbital period, CV class, or outburst type; however, higher cadence observations are necessary to test this, as the measured luminosity is dependent on the timing of the observations in these variable objects. The observations show that the previously detected radio emission from SS Cyg is not unique in type, luminosity (in the plateau phase of the outburst), or variability time-scales. Our results prove that DN, as a class, are radio emitters in outburst.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.588
Threshold uncertainty score0.628

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 science0.0010.000
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 head0.012
GPT teacher head0.202
Teacher spread0.190 · 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

Citations55
Published2016
Admission routes2
Has abstractyes

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