MétaCan
Menu
Back to cohort
Record W2081943772 · doi:10.1088/0004-637x/762/1/8

MESA MODELS OF CLASSICAL NOVA OUTBURSTS: THE MULTICYCLE EVOLUTION AND EFFECTS OF CONVECTIVE BOUNDARY MIXING

2012· article· en· W2081943772 on OpenAlexaff
Pavel A. Denissenkov, Falk Herwig, Lars Bildsten, Bill Paxton

Bibliographic record

VenueThe Astrophysical Journal · 2012
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAstrophysical Phenomena and Observations
Canadian institutionsUniversity of VictoriaTRIUMF
Fundersnot available
KeywordsWhite dwarfPhysicsAstrophysicsNova (rocket)Accretion (finance)ConvectionStellar evolutionDwarf novaMixing (physics)StarsMechanics

Abstract

fetched live from OpenAlex

Novae are cataclysmic variables driven by accretion of H-rich material onto a white-dwarf (WD) star from its low-mass main-sequence binary companion. New time-domain observational capabilities, such as the Palomar Transient Factory and Pan-STARRS, have revealed a diversity of their behaviour that should be theoretically addressed. Nova outbursts depend sensitively on nuclear physics data, and more readily available nova simulations are needed in order to effectively prioritize experimental effort in nuclear astrophysics. In this paper we use the MESA stellar evolution code to construct multicycle nova evolution sequences with CO WD cores. We explore a range of WD masses and accretion rates as well as the effect of different cooling times before the onset of accretion. In addition, we study the dependence on the elemental abundance distribution of accreted material and convective boundary mixing at the core-envelope interface. Models with such convective boundary mixing display an enrichment of the accreted envelope with C and O from the underlying white dwarf that is commensurate with observations. We compare our results with the previous work and investigate a new scenario for novae with the 3He-triggered convection.

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.614
Threshold uncertainty score0.363

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 studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.014
GPT teacher head0.240
Teacher spread0.226 · 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 designTheoretical or conceptual
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

Citations95
Published2012
Admission routes1
Has abstractyes

Explore more

Same venueThe Astrophysical JournalSame topicAstrophysical Phenomena and ObservationsFrench-language works237,207