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Record W4400454153 · doi:10.3847/1538-4357/ad4d54

The Long-period Spectroscopic Orbit and Dust Creation in the Wolf–Rayet Binary System WR 125

2024· article· en· W4400454153 on OpenAlexaff
Noel D. Richardson, Andrea R. Daly, P. M. Williams, Grant M. Hill, В. И. Шенаврин, Izumi Endo, André-Nicolas Chené, Nicole Karnath, Ryan M. Lau, A. F. J. Moffat, G. Weigelt

Bibliographic record

VenueThe Astrophysical Journal · 2024
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAstrophysics and Star Formation Studies
Canadian institutionsUniversité de Montréal
FundersEmbry-Riddle Aeronautical UniversityArizona Space Grant ConsortiumUniversities Space Research AssociationResearch Corporation for Science Advancement
KeywordsPhysicsPhotometry (optics)AstrophysicsWolf–Rayet starOrbital periodAstronomyStars

Abstract

fetched live from OpenAlex

Abstract Several long-period binaries with a carbon-rich Wolf–Rayet star and an OB star produce dust in their wind collisions. In eccentric binaries, this is seen most strongly near periastron passage. The exact conditions leading to dust creation require the orbital properties to be determined, which is difficult owing to their long periods. Recently, the binary system WR 125 (WC7 + O9III) began a dust-creation episode seen through an infrared outburst first detected by NEOWISE-R, which was the first outburst detected since 1991. We present new near- and mid-infrared photometry, which we use to show consistency between the two outbursts and derive an orbital period of 28.12 − 0.05 + 0.10 yr. We use a long time series of optical spectra to place the first constraints on its orbital elements, on the assumption that this system will produce dust near periastron. The orbit has a mild eccentricity of 0.29 ± 0.12 and is only derived for the Wolf–Rayet component, as the O star’s radial velocities have noise that is likely larger than the expected semiamplitude of the orbit. We also present SOFIA/FORCAST grism spectroscopy to examine the infrared spectral energy distribution of the dust during this outburst, comparing its properties to other WCd binaries, and deriving a dust temperature of 580 K in 2021. This collection of observations will allow us to plan future observations of this system and place the system in the context of dust-creating Wolf–Rayet binaries.

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)0.000
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 score0.005
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.007
GPT teacher head0.244
Teacher spread0.237 · 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

Citations3
Published2024
Admission routes1
Has abstractyes

Explore more

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