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ZENODO
Dataset . 2025
License: CC BY
Data sources: ZENODO
ZENODO
Dataset . 2025
License: CC BY
Data sources: Datacite
ZENODO
Dataset . 2025
License: CC BY
Data sources: Datacite
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Reproducibility package for: "Nuclear Neural Networks: Emulating late burning stages in Core Collapse Supernova Progenitors"

Authors: Grichener, Aldana;

Reproducibility package for: "Nuclear Neural Networks: Emulating late burning stages in Core Collapse Supernova Progenitors"

Abstract

Reproducibility package for: "Nuclear Neural Networks: Emulating late burning stages in Core Collapse Supernova Progenitors". It contains mesa stellar models used to determine the parameter space of the training sets, training sets, trained nuclear neural network (NNN) models, test datasets, and python scripts used for the analysis performed in this manuscript, including scripts and result files used to generate the figures. Detailed documentation on how to reproduce our results, along with guidelines on how to use and/or create NNNs for your own science can be found in this guide. The complete BBQ runs that include additional timesteps for training the NNNs and datasets for extended density ranges, comprising a total of 4TB, will be shared upon request from the corresponding author.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average