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Record W1620778208 · doi:10.1103/physrevc.90.038801

Strength of the<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mrow><mml:msub><mml:mi>E</mml:mi><mml:mi>R</mml:mi></mml:msub><mml:mo>=</mml:mo><mml:mn>127</mml:mn></mml:mrow></mml:math>keV,<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mmultiscripts><mml:mi mathvariant="normal">Al</mml:mi><mml:mprescripts/><mml:none/><mml:mrow><mml:mn>26</mml:mn></mml:mrow></mml:mmultiscripts><mml:mo>(</mml:mo><mml:mi>p</mml:mi><mml:mo>,</mml:mo><mml:mi>γ</mml:mi><mml:mo>)</mml:mo><mml:mmultiscripts><mml:mi mathvariant="normal">Si</mml:mi><mml:mprescripts/><mml:none/><mml:mrow><mml:mn>27</mml:mn></mml:mrow></mml:mmultiscripts></mml:math>resonance

2014· article· lv· W1620778208 on OpenAlexaff
A. Parikh, J. José, A. Karakas, C. Ruiz, K. Wimmer

Bibliographic record

VenuePhysical Review C · 2014
Typearticle
Languagelv
FieldPhysics and Astronomy
TopicX-ray Spectroscopy and Fluorescence Analysis
Canadian institutionsTRIUMF
Fundersnot available
KeywordsArtificial intelligenceAlgorithmMathematicsComputer science

Abstract

fetched live from OpenAlex

We examine the impact of the strength of the ${E}_{R}=127$ keV, $^{26}\mathrm{Al}(p,\ensuremath{\gamma})^{27}\mathrm{Si}$ resonance on $^{26}\mathrm{Al}$ production in classical nova explosions and asymptotic giant branch (AGB) stars. Thermonuclear $^{26}\mathrm{Al}(p,\ensuremath{\gamma})^{27}\mathrm{Si}$ reaction rates are determined using different assumed strengths for this resonance and representative stellar model calculations of these astrophysical environments are performed using these different rates. Predicted $^{26}\mathrm{Al}$ yields in our models are not sensitive to differences in rates determined using zero and a commonly stated upper limit corresponding to $\ensuremath{\omega}{\ensuremath{\gamma}}_{\mathrm{UL}}=0.0042$ $\ensuremath{\mu}\mathrm{eV}$ for this resonance strength. Yields of $^{26}\mathrm{Al}$ decrease by 6% and, more significantly, up to 30%, when a strength of $24\ifmmode\times\else\texttimes\fi{}\ensuremath{\omega}{\ensuremath{\gamma}}_{\mathrm{UL}}=0.1$ $\ensuremath{\mu}\mathrm{eV}$ is assumed in the adopted nova and AGB star models, respectively. Given that the value of $\ensuremath{\omega}{\ensuremath{\gamma}}_{\mathrm{UL}}$ was deduced from a single, background-dominated $^{26}\mathrm{Al}(^{3}\mathrm{He},d)^{27}\mathrm{Si}$ experiment where only upper limits on differential cross sections were determined, we encourage new experiments to confirm the strength of the 127-keV resonance.

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)0.009
metaresearch head score (Gemma)0.008
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Meta-epidemiology (broad), Science and technology studies, Scholarly communication, Open science, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Science and technology studies, Open science, Research integrity, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.850
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0090.008
Meta-epidemiology (narrow)0.0060.011
Meta-epidemiology (broad)0.0030.013
Bibliometrics0.0030.007
Science and technology studies0.0090.010
Scholarly communication0.0080.009
Open science0.0140.012
Research integrity0.0100.011
Insufficient payload (model declined to judge)0.4590.013

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 head0.245
Teacher spread0.228 · 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; both teacher heads agree on what is shown here.

Study designBench or experimental
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

Citations5
Published2014
Admission routes1
Has abstractyes

Explore more

Same venuePhysical Review CSame topicX-ray Spectroscopy and Fluorescence AnalysisFrench-language works237,207