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Record W2768923717 · doi:10.1051/0004-6361/201732212

Spin rates and spin evolution of O components in WR+O binaries

2018· article· en· W2768923717 on OpenAlexaff
D. Vanbeveren, N. Mennekens, Michael M. Shara, A. F. J. Moffat

Bibliographic record

VenueAstronomy and Astrophysics · 2018
Typearticle
Languageen
FieldPhysics and Astronomy
TopicStellar, planetary, and galactic studies
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsAstrophysicsRoche lobePhysicsCommon envelopeRadiative transferStarsBinary numberStellar evolutionWhite dwarfAstronomyQuantum mechanics

Abstract

fetched live from OpenAlex

Context.Despite 50 yr of extensive binary research, we must conclude that the Roche lobe overflow/mass transfer process that governs close binary evolution is still poorly understood. Aims.It is the scope of the present paper to lift the edge of the veil by studying the spin-up and spin-down processes of the O-type components of WR+O binaries. Methods.We critically analyzed the available observational data of rotation speeds of the O-type components in WR+O binaries. By combining a binary evolutionary code and a formalism that describes the effects of tides in massive stars with an envelope in radiative equilibrium, we computed the corresponding rotational velocities during the Roche lobe overflow of the progenitor binaries. Results.In all the WR+O binaries studied, we find that the O-type stars were affected by accretion of matter during Roche lobe overflow (RLOF) of the progenitor. This means that common envelope evolution, which excludes any accretion onto the secondary O star, has not played an important role in explaining WR+O binaries. Moreover, although it is very likely that the O-type star progenitors were spun up by mass transfer, many ended the RLOF (and mass transfer) phase with a rotational velocity that is significantly smaller than the critical rotation speed. This may indicate that during the mass transfer phase there is a spin-down process that is of the same order, although significantly less, than that of the spin-up process. We propose a Spruit–Tayler type dynamo spin-down suggested in the past to explain the rotation speeds of the mass gainers in long-period Algols.

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)0.001
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 score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
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 head0.012
GPT teacher head0.225
Teacher spread0.213 · 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

Citations21
Published2018
Admission routes1
Has abstractyes

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