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@MISC{Hilgers:916498,
      author       = {Hilgers, Robin and Wortmann, Daniel and Blügel, Stefan},
      title        = {{D}ata processing for the {J}u{H}emd database and
                      {ML}-training and evaluation scripts},
      reportid     = {FZJ-2022-06287},
      year         = {2022},
      note         = {MIT license},
      abstract     = {This software publication contains python code which: 1.
                      Process the JuHemd (see related identifiers) database so
                      that complete data points are selected to be processed in a
                      machine readable and ML-ready format. A magnetic threshold
                      of 0.1 Bohr magneton as total absolute magnetic moment is
                      applied to the data. Data points with zero Curie
                      temperatures are excluded. The script produces data arrays
                      in randomized order and uses supplemental atomic data. The
                      supplemental atomic data as well as the generated data set
                      is published separately (see related identifiers). The data
                      is generated once including density-functional theory
                      generated descriptors and once excluding them. 2. Is needed
                      to train and evaluate ML-models demonstrating the use of the
                      data for the prediction of Curie temperatures as described
                      in our upcoming paper.},
      cin          = {IAS-1 / PGI-1},
      cid          = {I:(DE-Juel1)IAS-1-20090406 / I:(DE-Juel1)PGI-1-20110106},
      pnm          = {5211 - Topological Matter (POF4-521) / HDS LEE - Helmholtz
                      School for Data Science in Life, Earth and Energy (HDS LEE)
                      (HDS-LEE-20190612)},
      pid          = {G:(DE-HGF)POF4-5211 / G:(DE-Juel1)HDS-LEE-20190612},
      typ          = {PUB:(DE-HGF)33},
      url          = {https://juser.fz-juelich.de/record/916498},
}