MISTY MASI: Metadata-Assisted Scholarly Intelligence — From Concept to Persistent Scholarly Artifact

High-resolution academic reference poster introducing MISTY MASI (Metadata-Assisted Scholarly Intelligence), an open, metadata-driven workflow for transforming research ideas into persistent scholarly artifacts. The poster explains the complete publication lifecycle from concept formation, canonical narrative development, academic poster creation, metadata authoring, GitHub repository seeding, DOI minting through Zenodo, cryptographic integrity using SHA-256, OpenTimestamps (OTS), and long-term scholarly preservation. It introduces the MASI methodology, explains the underlying technologies including Git, GitHub, GitHub CLI, Zenodo, Digital Object Identifiers (DOIs), Concept DOIs, Version DOIs, OpenTimestamps, blockchain-backed timestamp verification, cryptographic hashes, and machine-readable metadata. The poster includes a complete publication architecture, repository layout, publication workflow, sample publication descriptor template, publication automation script, guidance for obtaining and configuring a Zenodo access token, recommendations for Linux, Windows, WSL, macOS, Docker, GitHub Codespaces, Google Colab, Jupyter Notebooks, HPC clusters and cloud environments, and demonstrates how generative AI can assist researchers in drafting metadata while preserving human responsibility for scholarly accuracy. The publication serves simultaneously as a reference architecture, reproducibility guide, educational tutorial, onboarding manual, and practical implementation guide for reproducible scholarly publishing using the Misty DOI ecosystem.