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ZENODO
Dataset . 2024
License: CC BY
Data sources: ZENODO
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
ZENODO
Dataset . 2025
License: CC BY
Data sources: ZENODO
ZENODO
Dataset . 2024
License: CC BY
Data sources: Datacite
ZENODO
Dataset . 2025
License: CC BY
Data sources: Datacite
ZENODO
Dataset . 2025
License: CC BY
Data sources: Datacite
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Claim

Machine Learning Predicts Meter-Scale Laboratory Earthquakes

Research datakeyboard_double_arrow_right Dataset 26 Sep 2024 English Publisher:Zenodo
Authors: Norisugi, Reiju; Kaneko, Yoshihiro; Rouet-Leduc, Bertrand;

doi: 10.5281/zenodo.13768729 , 10.5281/zenodo.13768728 , 10.5281/zenodo.14925543

Machine Learning Predicts Meter-Scale Laboratory Earthquakes

Abstract

Numerical data and Python scripts used to make Figures in the manuscript entitled "Machine Learning Predicts Meter-Scale Laboratory Earthquakes". We provide the data and scripts to create Figures 1 to 6 from the main text and Figures S1 to S9 from the supplementary information. Note that you should download the experimental catalog of Yamashita et al. (Nature Comm, 2021) and address the request for shear force data to Futoshi Yamashita, the organizer of the target experiment.

Related Organizations
Keywords

Machine learning, Seismology, Large-scale rock friction laboratory experiment, Earthquake cycle

  • BIP!
    Impact byBIP!
    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).
    		 1
    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.
    		 Average
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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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!
1
Average
Average
Average