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cff-version: 1.2.0
title: >-
  MatFold: Cross-validation Protocols for Materials Science Data 
message: >-
  If you use this software, please cite it using the
  metadata from this file and/or cite the publication.
type: software
authors:
  - given-names: Peter
    family-names: Schindler
    email: p.schindler@northeastern.edu
    affiliation: Northeastern University
    orcid: 'https://orcid.org/0000-0002-1319-6570'
  - given-names: Matthew
    name-particle: D.
    family-names: Witman
    orcid: 'https://orcid.org/0000-0001-6263-5114'
    email: mwitman@sandia.gov
    affiliation: Sandia National Laboratories
identifiers:
  - type: doi
    value: 10.5281/zenodo.13147391
    description: Zenodo Record
  - type: doi
    value: 10.26434/chemrxiv-2024-bmw1n
    description: Preprint
  - type: doi
    value: 10.1039/D4DD00250D
    description: Peer-reviewed Publication
repository-code: 'https://github.com/d2r2group/MatFold/'
abstract: >-
  This is a Python package for gaining systematic insights
  into materials discovery models' performance through
  standardized, reproducible, and featurization-agnostic
  chemical and structural cross-validation protocols.
keywords:
  - machine learning
  - materials science
  - cross-validation
  - generalization error
license: MIT
commit: 897768f1795b83ce0cce72937027949b2959d3fd
version: v1.2.3
date-released: '2024-11-26'
