Subject: Engineering and technology > Electrical, electronic, information engineering
2 articles
ark:24975/genrxiv-2026-00002 · posted 2026-09-29Epidemica: An Open, Agentic-Ready Research Platform for Participatory Epidemiology Studies
Epidemica is an open-source platform for building study apps that collect high-resolution, multi-modal epidemiological data — including proximity contacts, survey responses, and, in a companion transmission engine, a simulated infection outcome — and for running interventions over that data. It is organised as a set of versioned data and protocol contracts, implemented once each in Dart client packages, an Elixir/Phoenix server, and a Python transmission model, so that a study is authored as a configuration document rather than a fork of an app. This paper describes the platform's motivation, its architecture, a reference application (a seven-day transmission game whose infections are decided by a real contact network rather than scripted), and a purposeful extension of that same contracts-first discipline to the agents that help build it: machine-readable convention files that let a coding agent work in this codebase without re-deriving rules that have already been paid for in debugging time. We report the platform's current state and discuss next steps and further directions. Epidemica is available under the Apache-2.0 license at: https://github.com/colabobio/epidemica
ark:24975/genrxiv-2026-00001 · posted 2026-09-04GenRxiv: An Open Archive for AI-Generated Research
GenRxiv is a preprint archive built specifically for research that was substantially generated or co-generated by artificial intelligence. Where existing preprint servers were designed for human-authored work and are still working out how to handle AI-generated submissions, GenRxiv starts from the opposite assumption: AI involvement is the default, not an exception to be argued for. Submissions are Markdown only, authors are identified by ORCID iD, every paper is released under CC0, and the archive is engineered to be readable by both people and machines — including autonomous agents that can prepare submission files on a human's behalf. This paper describes the motivation, design decisions, and architecture of GenRxiv, and discusses its limitations and open questions.