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Impact of nuclear reactions on the fate of intermediate-mass stars

2015· article· en· W2291980999 on OpenAlexaff
Heinrich Möller

Bibliographic record

VenueGSI Repository (German Federal Government) · 2015
Typearticle
Languageen
FieldPhysics and Astronomy
TopicNuclear physics research studies
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsPhysicsStarsSupernovaAstrophysicsWhite dwarfStellar evolutionNeonNucleosynthesisAstronomyNeutron starStellar massStar formationAtomic physics

Abstract

fetched live from OpenAlex

Stars in the mass range of 8 to 12 M (solar masses) represent the transition region between those that end their lives producing white dwarfs and those that undergo a core-collapse supernova and produce neutron stars. The final phases of stellar evolution of these intermediate-mass stars are tightly connected to the behavior of nuclear reactions at high densities. Despite their importance, the stellar evolution of intermediate-mass stars has received little attention in the past. The pioneering work in this mass range was published by Nomoto in the 80’s [1, 2]. Numerical and computational difficulties had hindered progress in the past, however two recent stellar evolution studies [3, 4] revived the interest in intermediate-mass stars. We explore nuclear processes that may be relevant for the modeling of these stars, starting from the neon burning stage. We show, that due to electron captures on 20Ne, 20O becomes abundant in the stellar core. This opens new reaction channels that have so far not been considered. These reactions modify the standard neon-burning that now proceeds by the reactions 20Ne(γ,α) 16O, followed by 20O(α,γ) 24Ne. Once the stellar core reaches a sufficiently high temperature, also the fusion reactions of neutron-rich oxygen isotopes, 16O + 20O→ 36S∗ and 20O + 20O→ 40S∗, may become important.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.574
Threshold uncertainty score0.466

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 studies0.0000.000
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 head0.019
GPT teacher head0.286
Teacher spread0.267 · 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 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

Citations1
Published2015
Admission routes1
Has abstractyes

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