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Non-thermal emission in Wolf-Rayet stars: are massive companions required?

2000· article· en· W2162545417 on OpenAlexaff
S. M. Dougherty, P. M. Williams

Bibliographic record

VenueMonthly Notices of the Royal Astronomical Society · 2000
Typearticle
Languageen
FieldPhysics and Astronomy
TopicStellar, planetary, and galactic studies
Canadian institutionsUniversity of CalgaryHerzberg Institute of Astrophysics
Fundersnot available
KeywordsPhysicsStarsWolf–Rayet starAstrophysicsOpacityThermalAstronomyO-type starStellar classificationThermal emissionMeteorology

Abstract

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We examine the radio spectral indices of 23 Wolf-Rayet (WR) stars to identify the nature of their radio emission. We identify nine systems as non-thermal emitters. In seven of these systems the non-thermal emission dominates the radio spectrum, while in the remaining two it is of comparable strength to the thermal, stellar wind emission, giving ‘composite’ spectra. Among these nine systems, seven have known spectroscopic or visual binary companions. The companions are all massive O or early B-type stars, strongly supporting a connection between the appearance of non-thermal emission in WR stars and the presence of a massive companion. In three of these binaries, the origin of non-thermal emission in a wind-collision region between the stars has been well established in earlier work. The binary systems that exhibit only thermal emission are all short-period systems where a wind-collision zone is deep within the opaque region of the stellar wind of the WR star. To detect non-thermal emission in these systems requires optically thin lines of sight to the wind-collision region.

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 score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
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 integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.009
GPT teacher head0.210
Teacher spread0.201 · 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

Citations144
Published2000
Admission routes1
Has abstractyes

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