Computational · Paper · 2026

A template/ approach to Reproducible Generative Research

Zenodo

Catalog Row123
Citation KeyFriedman2026TemplateApproachReproducibleGenerative123
Paper FolderAvailable
DOI10.5281/zenodo.20419007
Platform availability

Overview

Extracted from the local paper documentation when available.

The reproducibility crisis in computational research is fundamentally structural: research artifacts are scattered across disconnected tools—LaTeX editors, Jupyter notebooks, ad-hoc shell scripts—with no enforced mechanism to keep code, data, and manuscript synchronized. Studies have shown that most published findings are false positives, replication rates in psychology hover around 36%, and only ...

reproducible researchinfrastructure-as-codesteganographycryptographic provenanceLaTeX renderingmodular infrastructurepublication integrityzero-mock testingthin orchestratortwo-layer architectureFAIR4RSresearch software engineering

Use Notes

Concise findings and methods pulled from README/SKILL documentation.

Findings / Concepts
  • The reproducibility crisis in computational research is fundamentally structural: research artifacts are scattered across disconnected tools—LaTeX editors, Jupyter notebooks, ad-hoc shell scripts—with
  • Studies have shown that most published findings are false positives, replication rates in psychology hover around 36%, and only 24% of 1.4 million Jupyter notebooks can be successfully re-executed.
Methods / Techniques
  • Software pipeline design
  • Data-driven analysis

Citation

Plain-text citation for quick reuse.

Friedman, Daniel Ari. 2026. A template/ approach to Reproducible Generative Research. Zenodo. DOI: 10.5281/zenodo.20419007. URL: https://doi.org/10.5281/zenodo.20419007.

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