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Copy file name to clipboardExpand all lines: src/pages/about.astro
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@@ -16,7 +16,6 @@ import merkleTrees from '../assets/Merkle.png';
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const title ="About - The Insight Journal";
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const description ="Learn about the Insight Journal's mission, technology, and how to contribute to open, reproducible medical image analysis research.";
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const currentYear =newDate().getFullYear();
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const lastModified =newDate();
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---
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@@ -104,7 +103,7 @@ const lastModified = new Date();
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<li><strong>Verifiable Provenance:</strong> Cryptographic identifiers (<ahref="https://dpid.org"target="_blank"rel="noopener noreferrer">DPIDs</a>) and blockchain-based
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records create tamper-proof provenance for all contributions.</li>
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<li><strong>Community Governance:</strong> Decision-making power resides with the community,
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not corporate publishers. The journal's future belongs to its users.</li>
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not corporate publishers. The journal's future belongs to its contributors.</li>
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<li><strong>Sustainability:</strong> Built on open-source principles with cost-effective
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infrastructure designed for long-term preservation and community ownership.</li>
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</ul>
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These technologies all share a common foundation: <ahref="https://en.wikipedia.org/wiki/Merkle_tree"target="_blank"rel="noopener noreferrer">Merkle trees</a>, which provide cryptographic
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verification and tamper-proof records. Every change, every version, every contribution is
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permanently and verifiably recorded.
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<br />
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<i>Post-publication manipulations are impossible without detection.</i>
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<strong>This ensures integrity, transparency, and trustworthiness</strong>
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</p>
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<h3>FAIR by Design</h3>
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rich, interactive content that transforms articles from static PDFs into engaging, explorable research artifacts.
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</p>
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<p>
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MyST Markdown's structured yet human-readable format makes research exceptionally accessible to AI systems and large language models (LLMs).
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Unlike proprietary formats or PDFs that obscure content structure, MyST preserves semantic meaning through its markup—equations remain
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interpretable, code blocks are clearly delineated, and citations maintain their relationships. This machine-readability enables AI agents
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<strong>MyST Markdown's structured yet human-readable format makes research exceptionally accessible to AI systems and large language models (LLMs).</strong>
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Unlike proprietary formats or PDFs that obscure content structure, MyST <strong>preserves semantic meaning</strong> through its markup—equations remain
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interpretable, code blocks are clearly delineated, and citations maintain their relationships. This <strong>machine-readability</strong> enables AI agents
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to accurately extract methodologies, reproduce analyses, generate summaries, and synthesize findings across multiple papers.
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</p>
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<p>
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As research increasingly leverages AI for literature review, meta-analysis, and automated hypothesis generation, MyST's transparent structure ensures
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that published knowledge remains computationally accessible for decades to come, bridging human scholarship and artificial intelligence.
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As research increasingly leverages AI for literature review, meta-analysis, and automated hypothesis generation, <strong>MyST's transparent structure ensures
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that published knowledge remains computationally accessible for decades to come</strong>, bridging human scholarship and artificial intelligence.
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