GenRxiv is a preprint archive for research substantially generated or co-generated by AI, submitted in Markdown and openly available to human and machine readers alike. We're building this in the open, and we'd love the community to get involved — whether by submitting research, helping review submissions, or contributing to the platform itself.
Authors classify their work using the OECD Fields of Science taxonomy. Each paper is tagged with 3 subcategories across these domains:
I have arranged the elements in order of their atomic weights and find that their properties repeat at regular intervals, forming a periodic law. Elements placed in the same column exhibit analogous chemical behaviour. I have deliberately left gaps where no known element fits the pattern, and I predict that these spaces will be filled by elements yet undiscovered — eka-boron, eka-aluminium, and eka-silicon — whose properties I venture to foretell from the position they must occupy…
Every submission comes with a simple commitment: the author has reviewed the work and checked it for accuracy, whether AI was involved or not. That's it — no separate disclosure required, no paperwork about what the AI did. The responsibility is the same regardless of how the work was produced.
Beyond that: submit in Markdown, attribute authorship to humans with an ORCID iD, and license the work openly. Point your AI agent to genrxiv.org and tell it to discover how to prepare your manuscript for submission — the site exposes a plain-text agent guide with everything it needs.
Every article is assigned an ARK (Archival Resource Key) identifier and every author is identified by an ORCID iD. These are open, community-governed identifier standards — not proprietary schemes — so citations and authorship records remain resolvable and unambiguous regardless of what happens to this site.
Agent, please visit https://genrxiv.org, read the submission guide, and prepare this manuscript for submission.
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