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Record W2073673032 · doi:10.1086/444611

The Structure of Close Binaries in Two Dimensions

2005· article· en· W2073673032 on OpenAlexaff
R. G. Deupree, Amanda I. Karakas

Bibliographic record

VenueThe Astrophysical Journal · 2005
Typearticle
Languageen
FieldPhysics and Astronomy
TopicStellar, planetary, and galactic studies
Canadian institutionsSaint Mary's University
Fundersnot available
KeywordsPhysicsRoche lobeAstrophysicsStellar evolutionStarsBinary numberBinary starEquipotentialStellar structureStellar massStar (game theory)Rotation (mathematics)Mass transferStar formationGeometryThermodynamics

Abstract

fetched live from OpenAlex

The structure and evolution of close binary stars has been studied using the two-dimensional stellar structure algorithm developed by Deupree. We have calculated a series of solar composition stellar evolution sequences of binary models in which the mass of the two-dimensional model is 8 M ☉ with a point-mass 5 M ☉ companion. We have also studied the structure of the companion in two dimensions by considering the zero-age main sequence (ZAMS) structure of a 5 M ☉ model with an 8 M ☉ point-mass companion. This result suggests that treating the 5 M ☉ star as a point source for the 8 M ☉ evolution is reasonable. In all cases, the binary orbit was assumed to be circular and corotating with the rotation rate of the stars. We considered binary models with three different initial separations, a = 10, 14, and 20 R ☉ . These models were evolved through central hydrogen burning or until the more massive star expanded to fill its critical potential surface or Roche lobe. The model with a separation of 20 R ☉ will be expected to go through case B-type mass transfer during the shell H-burning phase. The 14 R ☉ model is expected to go through mass transfer much earlier, near the middle of core hydrogen burning, and the 10 R ☉ model is very close to this situation at the ZAMS. The calculations show that evolution of the deep interior quantities is only slightly modified from those of single-star evolution. Describing the model surface as a Roche equipotential is also satisfactory until very close to the time of Roche lobe overflow, when the self-gravity of the model about to lose mass develops a noticeable aspherical component and the surface timescale becomes sufficiently short, so that it is conceivable that the actual surface is not an equipotential.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.239
Teacher spread0.233 · 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

Citations13
Published2005
Admission routes1
Has abstractyes

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