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Record W3093724489 · doi:10.1093/mnrasl/slaa190

An evidence-based assumption that helps to reduce the discrepancy between the observed and predicted 7Be abundances in novae

2020· article· en· W3093724489 on OpenAlexafffund
Pavel A. Denissenkov, C. Ruiz, S. Upadhyayula, Falk Herwig

Bibliographic record

VenueMonthly Notices of the Royal Astronomical Society Letters · 2020
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAstrophysical Phenomena and Observations
Canadian institutionsUniversity of VictoriaTRIUMF
FundersNatural Sciences and Engineering Research Council of CanadaNational Science Foundation
KeywordsEjectaNova (rocket)AstrophysicsHydrostatic equilibriumMass fractionPhysicsAbundance (ecology)Fraction (chemistry)SpectroscopyEnvelope (radar)ChemistrySupernovaThermodynamicsAstronomyChromatography

Abstract

fetched live from OpenAlex

ABSTRACT Recent spectroscopic measurements of the equivalent widths of the resonant Be ii doublet and Ca ii K lines and their ratios in expanding nova ejecta indicate surprisingly high abundances of 7Be with a typical mass fraction Xobs(7Be) = 10−4. This is an order of magnitude larger than theoretically predicted values of Xtheor(7Be) ∼ 10−5 for novae. We use an analytical solution of the 7Be production equations to demonstrate that Xtheor(7Be) is proportional to the 4He mass fraction Y in the nova accreted envelope and then we perform computations of 1D hydrostatic evolution of the $1.15\, \mathrm{M}_\odot$ CO nova model that confirm our conclusion based on the analytical solution. Our assumption of enhanced 4He abundances helps to reduce, although not completely eliminate, the discrepancy between Xobs(7Be) and Xtheor(7Be). It is supported by ultraviolet, optical, and infrared spectroscopy data that reveal unusually high values of Y in nova ejecta. We also show that a significantly increased abundance of 3He in nova accreted envelopes does not lead to higher values of Xtheor(7Be) because this assumption affects the evolution of nova models resulting in a decrease of both their peak temperatures and accreted masses and, as a consequence, in a reduced production of 7Be.

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)0.002
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.043
GPT teacher head0.244
Teacher spread0.201 · 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 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

Citations12
Published2020
Admission routes2
Has abstractyes

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