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Record W2067437743 · doi:10.1086/498224

Composition of the Innermost Core‐Collapse Supernova Ejecta

2006· article· en· W2067437743 on OpenAlexaff
Carla Fröhlich, Peter C. Hauser, M. Liebendörfer, G. Martı́nez-Pinedo, F.‐K. Thielemann, Eduardo Bravo, N. T. Zinner, W. R. Hix, K. Langanke, Anthony Mezzacappa, K. Nomoto

Bibliographic record

VenueThe Astrophysical Journal · 2006
Typearticle
Languageen
FieldPhysics and Astronomy
TopicNeutrino Physics Research
Canadian institutionsCanadian Institute for Theoretical AstrophysicsUniversity of Toronto
Fundersnot available
KeywordsPhysicsNeutrinoSupernovaEjectaNucleosynthesisAstrophysicsStarsNeutron starNuclear physics

Abstract

fetched live from OpenAlex

With currently known input physics and computer simulations in one dimension, a self-consistent treatment of core-collapse supernovae does not yet lead to successful explosions, while two-dimensional models show some promise. Thus, there are strong indications that the delayed neutrino mechanism works combined with a multidimensional convection treatment for unstable layers (possibly with the aid of rotation, magnetic fields and/or still existent uncertainties in neutrino opacities). On the other hand, there is a need to provide correct nucleosynthesis abundances for the progressing field of galactic evolution and observations of low-metallicity stars. The innermost ejecta is directly affected by the explosion mechanism, i.e., most strongly, the yields of Fe group nuclei for which an induced piston or thermal bomb treatment will not provide the correct yields because the effect of neutrino interactions is not included. We apply parameterized variations to the neutrino-scattering cross sections in order to mimic in one dimension the possible increase of neutrino luminosities caused by uncertainties in proto-neutron star convection. Alternatively, parameterized variations are applied to the neutrino absorption cross sections on nucleons in the "gain region" to mimic the increase in neutrino energy deposition enabled by convective turnover. We find that both measures lead to similar results, causing explosions and a Y e > 0.5 in the innermost ejected layers, due to the combined effect of a short weak-interaction timescale and a negligible electron degeneracy, unveiling the proton-neutron mass difference. We include all weak interactions (electron and positron capture, β-decay, neutrino and antineutrino capture on nuclei, and neutrino and antineutrino capture on nucleons) and present first nucleosynthesis results for these innermost ejected layers to discuss how they improve predictions for Fe group nuclei. The proton-rich environment results in enhanced abundances of 45 Sc, 49 Ti, and 64 Zn as required by chemical evolution studies and observations of low-metallicity stars, as well as appreciable production of nuclei in the mass range up to A = 80.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.261
Teacher spread0.247 · 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 designSimulation or modeling
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

Citations225
Published2006
Admission routes1
Has abstractyes

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