{
  "title": "A template/ approach to Reproducible Generative Research: Architecture and Ergonomics from Configuration through Publication",
  "version": "v3.5.1",
  "doi": "10.5281/zenodo.16903351",
  "doi_url": "https://doi.org/10.5281/zenodo.16903351",
  "zenodo_record": "https://zenodo.org/records/16903351",
  "record_id": "20932520",
  "publication_date": "2026-06-26",
  "resource_type": {
    "title": "Software",
    "type": "software"
  },
  "creators": [
    {
      "name": "Friedman, Daniel Ari",
      "affiliation": null
    }
  ],
  "description": "Research Project Template v3.5.1 Final metadata release for the public template publication sweep. Archives the root source state after all standalone template DOI/version writebacks. Keeps every public exemplar release and Zenodo record aligned in the generated publication matrix. Records the first Zenodo/GitHub publications for template_gold_refinement and template_literature_meta_analysis. Root gates passed: Ruff, mypy, strict template drift, publication records, confidentiality, generated-artifact guard, no-mocks, Bandit, skills checks, and hook smoke tests.",
  "keywords": [],
  "files": [
    {
      "name": "docxology/template-v3.5.1.zip",
      "size_bytes": 11204091,
      "checksum": "md5:8bae3ccb71b1ab4c95d0b60d254dc0a2",
      "download_url": "https://zenodo.org/api/records/20932520/files/docxology/template-v3.5.1.zip/content"
    }
  ],
  "related_resources": [],
  "github_repo": "",
  "source": "zenodo-only",
  "checked_at": "2026-06-30T23:26:12Z",
  "domain": "Computational",
  "type": "Paper",
  "methods": [
    {
      "name": "Software pipeline design",
      "description": "Applied software pipeline design approach"
    },
    {
      "name": "Data-driven analysis",
      "description": "Applied data-driven analysis approach"
    }
  ],
  "key_findings": [
    "Infrastructure-as-code research lifecycle: Two-Layer Architecture, eight-stage build pipeline, Zero-Mock testing, and Documentation Duality (README + AGENTS + SKILL)."
  ],
  "related_papers": [
    "2023_NSFReporting",
    "2023_NaturalAIBased",
    "2025_AuBI"
  ]
}