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Record W2068730892 · doi:10.1051/0004-6361/201117008

<i>r</i>-Java: an<i>r</i>-process code and graphical user interface for heavy-element nucleosynthesis

2011· article· en· W2068730892 on OpenAlexafffund
Camille Charignon, M. Kostka, Nico Koning, Prashanth Jaikumar, Rachid Ouyed

Bibliographic record

VenueAstronomy and Astrophysics · 2011
Typearticle
Languageen
FieldPhysics and Astronomy
TopicNuclear physics research studies
Canadian institutionsUniversity of Calgary
FundersNatural Sciences and Engineering Research Council of CanadaCalifornia State University Long BeachKillam Trusts
KeywordsPhysicsNucleosynthesisComputer scienceJavar-processSource codeEjectaComputational scienceOperating systemAstrophysicsSupernova

Abstract

fetched live from OpenAlex

We present r-Java, an r-process code for open use that performs r-process nucleosynthesis calculations. Equipped with a simple graphical user interface, r-Java is capable of carrying out nuclear statistical equilibrium (NSE), as well as static and dynamic r-process calculations, for a wide range of input parameters. In this introductory paper, we present the motivation and details behind r-Java and results from our static and dynamic simulations. Static simulations are explored for a range of neutron irradiation and temperatures. Dynamic simulations are studied with a parameterized expansion formula. Our code generates the resulting abundance pattern based on a general entropy expression that can be applied to both degenerate and non-degenerate matter, allowing us to track the rapid density and temperature evolution of the ejecta during the initial stages of ejecta expansion. At present, our calculations are limited to the waiting-point approximation. We encourage the nuclear astrophysics community to provide feedback on the code and related documentation, which is available for download from the website of the Quark-Nova Project: http://quarknova.ucalgary.ca/.

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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.832
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 studies0.0000.000
Scholarly communication0.0000.001
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 head0.023
GPT teacher head0.276
Teacher spread0.254 · 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 designOther design
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

Citations14
Published2011
Admission routes2
Has abstractyes

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