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Record W2790498524 · doi:10.22323/1.204.0057

The new KADoNiS v1.0 and its influence on the s-process

2015· article· en· W2790498524 on OpenAlexafffund
I. Dillmann

Bibliographic record

VenueProceedings of XIII Nuclei in the Cosmos — PoS(NIC XIII) · 2015
Typearticle
Languageen
FieldEngineering
TopicMaterial Science and Thermodynamics
Canadian institutionsTRIUMF
FundersNatural Sciences and Engineering Research Council of CanadaTRIUMFSchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen ForschungNational Science Foundation
KeywordsProcess (computing)Computer scienceProgramming language

Abstract

fetched live from OpenAlex

and is presently available for testing at HTTP://EXP-ASTRO.PHYSIK.UNI-FRANKFURT.DE/KADONIS1.0/.All available datasets between 1 H and 210 Bi and their energy dependence for kT = 5 -100 keV have been reviewed, updated, and evaluated.The main difference to previous releases of KADoNiS is the intensive work that has been put in the inclusion of new experimental energy-dependent cross sections which should make the extrapolations to higher and lower energies more reliable.Also a revision of the 197 Au(n, γ) cross section has been applied which is widely used as reference cross section for time-of-flight and activation measurements.Several recent measurements in the astrophysical energy range have led to a new recommended value used throughout KADoNiS v1.0 which is 3-5.4% higher than the previously adopted value.Datasets for the up to now missing light stable isotopes 6 Li, 10,11 B, and 17 O were added and recommendations based on experimental data given.The total number of datasets in the KADoNiS database increased from 370 to more than 440 which is mainly due to the inclusion of radioactive isotopes 1-2 mass units away from stability.Although no measurements are available for these cases, they play an important role in modern s-process calculations with higher neutron densities.To be able to use a consistent database for s-process simulations it was decided to include these isotopes in the new update and calculate semi-empirical recommended cross sections.In this update also indirect measurements, namely (γ,n) measurements complemented by Hauser-Feshbach predictions with constrained input, have been included which yielded new (n,γ) recommended values for e.g. the branchings at 85 Kr, 185 W, and 186 Re.For other branching isotopes, e.g. 63Ni, first direct experimental time-of-flight data yielded a factor of 2 higher cross section compared to the previously used theoretical prediction.The influences of the changes of the new (n,γ) cross sections on the weak s-process have been investigated.Whereas the differences after core He burning are within 20%, the impact of the new set of MACS on the s-process abundance distribution is much larger at the end of the shell C burning which leads to a "weaker" s-process efficiency.

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)0.005
metaresearch head score (Gemma)0.011
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: none
Teacher disagreement score0.032
Threshold uncertainty score0.107

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.011
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0030.002
Science and technology studies0.0010.001
Scholarly communication0.0040.006
Open science0.0050.004
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0320.028

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 head0.015
GPT teacher head0.227
Teacher spread0.212 · 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

Citations6
Published2015
Admission routes2
Has abstractyes

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