MétaCan
Menu
Back to cohort
Record W2073806760 · doi:10.1051/0004-6361:200810373

Modeling He-rich subdwarfs through the hot-flasher scenario

2008· article· en· W2073806760 on OpenAlexfundno aff

Bibliographic record

VenueAstronomy and Astrophysics · 2008
Typearticle
Languageen
FieldPhysics and Astronomy
TopicStellar, planetary, and galactic studies
Canadian institutionsnot available
FundersConsejo Nacional de Investigaciones Científicas y TécnicasPublic Health Agency of Canada
KeywordsConvectionMixing (physics)Context (archaeology)StarsHomogeneousDiffusionSubdwarfStellar evolutionConvective mixing

Abstract

fetched live from OpenAlex

We present 1D numerical simulations aimed at studying the hot-flasher scenario for the formation of He-rich subdwarf stars. Sequences were calculated for a wide range of metallicities and physical assumptions, such as the stellar mass at the moment of the helium core flash. This allows us to study the two previously proposed flavors of the hot-flasher scenario (“deep” and “shallow” mixing cases) and to identify a third transition type. Our sequences are calculated by solving simultaneously the mixing and burning equations within a diffusive convection picture, and in the context of standard mixing length theory. We are able to follow chemical evolution during deep-mixing events in which hydrogen is burned violently, and therefore able to present a homogeneous set of abundances for different metallicities and varieties of hot-flashers. We extend the scope of our work by analyzing the effects of non-standard assumptions, such as the effect of chemical gradients, extra-mixing at convective boundaries, possible reduction in convective velocities, or the interplay between difussion and mass loss. Particular emphasis is placed on the predicted surface properties of the models. We find that the hot-flasher scenario is a viable explanation for the formation and surface properties of He-sdO stars. Our results also show that, during the early He-core burning stage, element diffusion may produce the transformation of (post hot-flasher) He-rich atmospheres into He-deficient ones. If this is so, then we find that He-sdO stars should be the progenitors of some of the hottest sdB stars.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.464
Threshold uncertainty score1.000

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 studies0.0010.000
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 head0.017
GPT teacher head0.210
Teacher spread0.193 · 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.

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

Citations139
Published2008
Admission routes1
Has abstractyes

Explore more

Same venueAstronomy and AstrophysicsSame topicStellar, planetary, and galactic studiesFrench-language works237,207