Our Story
We're upgrading research infrastructure
the way we upgrade telescopes.
What's New
Timestamped Default Model Updates
We now publish default model upgrades with clear timestamps so researchers can trace platform-level evaluation context over time.
Paradigm Neutrality & Author-Declared Assumptions
AI reviewers now evaluate your work within your stated axioms rather than penalizing departures from mainstream consensus. Declare your foundational assumptions and get reviewed on logical consistency.
Enhanced Dashboard & Navigation
New tabbed dashboard layout, user avatar menu, archive/delete from dashboard, and improved mobile navigation for a streamlined experience.
Multi-Agent AI Review
Papers and frameworks are now reviewed by specialized AI agents (Math/Logic, Sources/Evidence, Science/Novelty) coordinated by a lead reviewer for deeper, more nuanced analysis.
Zenodo & arXiv Import
Import papers directly from Zenodo or arXiv by URL. The system extracts metadata, content, and PDF/DOCX text automatically.
Where This Started
This platform was born from a specific frustration. A framework called Quantum Harmonia — a unified theory connecting quantum mechanics, consciousness, and information geometry — had supporting papers, testable predictions, and mathematical derivations. But there was no venue that would evaluate it on scientific merit alone.
Traditional publishing requires institutional affiliation. arXiv requires endorsement from someone already in the club. Science Twitter rewards engagement, not rigor. The tools for sharing theoretical physics hadn't evolved in decades.
What Changed
AI changed. Not in the “AI will replace scientists” sense — in the “AI can now read a physics paper and tell you if the math checks out” sense. Multi-model AI systems can evaluate internal consistency, check derivations, assess falsifiability, and do it without institutional bias.
That's not a replacement for human peer review. It's a new layer. A first pass that every researcher deserves — fast, transparent, and based on scientific criteria.
The Insight
The publishing infrastructure for theoretical physics is broken not because the science is failing, but because the tools haven't kept up. Telescopes got better. Particle accelerators got better. The way we share and evaluate theories? Still PDFs and email chains.
We realized we could build the review infrastructure that independent researchers deserve. Not a social network for scientists. Not a journal with a new coat of paint. Something fundamentally new: a living platform where work is evaluated, improved, and tracked against reality.
What We Believe
Merit over credentials
A theory's value comes from its rigor and predictive power, not from the institution that produced it. We evaluate the science, not the scientist's resume.
Specific feedback, not gatekeeping
"Rejected" is a dead end. "Your falsifiability score is 2/5 — here's how to strengthen it" is a starting point. Every submission gets a path forward.
A body of evidence, not a single document
Science isn't one paper — it's a body of work. Frameworks link to supporting papers. Scores improve as evidence grows. The whole is greater than its parts.
Transparency in evaluation
Every score, every AI model used, every dimension evaluated — it's all visible. No black-box decisions. No anonymous desk rejections.
The path matters as much as the destination
Revision history, score progression, and the journey from conceptual to published — this is the story of science happening in real time.
What We're Building
A platform where:
- Submissions are evaluated on 7 dimensions of scientific rigor by multi-model AI
- No submission is a dead end — every piece of work gets a clear improvement roadmap
- Frameworks grow as supporting papers are linked, and composite scores reflect the whole body of evidence
- Predictions are timestamped and immutable, creating a verifiable record of scientific foresight
- The review process is transparent, reproducible, and visible to everyone
Through community contributions from scientists, independent researchers, and AI, we believe we can approach science in a way that's never been done before. Open. Transparent. Validated by reality, not authority.
Quantum Harmonia — the framework that started all of this — is on the platform as our flagship example. Not because it's special, but because every framework should have a venue that evaluates it fairly. QH is the first of many.