An integrated workflow using version control, code review, automated testing, structured logging, metadata-rich output, and standardized post-processing creates a FAIR-aligned provenance chain from code development to published figures in numerical physics simulations.
PLoS Biology 12(1), e1001745 (Jan 2014)
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fastml is an R package that enforces leakage-free preprocessing through guarded resampling and provides a unified interface for safer automated ML including survival analysis.
Mathematical proofs are inherently reproducible by nature, unlike computational experiments which require shared code for equivalent scientific diligence.
citing papers explorer
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From Code to Figure: A FAIR-Aligned Data Provenance Chain for Reproducible Simulation Research in Numerical Physics
An integrated workflow using version control, code review, automated testing, structured logging, metadata-rich output, and standardized post-processing creates a FAIR-aligned provenance chain from code development to published figures in numerical physics simulations.
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fastml: Guarded Resampling Workflows for Safer Automated Machine Learning in R
fastml is an R package that enforces leakage-free preprocessing through guarded resampling and provides a unified interface for safer automated ML including survival analysis.
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Truth, Proof, and Reproducibility: There's no counter-attack for the codeless
Mathematical proofs are inherently reproducible by nature, unlike computational experiments which require shared code for equivalent scientific diligence.