Honest Review
Evaluates rigor, not orthodoxy
Specialist AI agents evaluate scientific rigor — consistency, math validity, falsifiability — without judging whether your theory is “mainstream.” Paradigm neutrality is built in.
Opening in April 2026
We're welcoming early researchers to help shape the platform. Sign up below or reach out directly.
theoryofeverything.ai
Submit your theoretical framework. Specialist AI agents review your math, sources, and science independently. Build a living body of work with linked papers and versioned reviews. No gatekeeping — just rigorous, paradigm-neutral review. We judge your logic, not your orthodoxy.
The Iteration Effect
3.6
First review
3.8
Latest review
Across 15 works with multiple reviews, authors improved their scores by an average of +0.2 points over 28 total iterations. 7 out of 15 works showed improvement.
Average gain per iteration: +0.10 points
4
Frameworks submitted
31
Papers submitted
78
Reviews completed
8
Models in rotation
4
AI providers
Every submission is evaluated across seven dimensions of scientific rigor. No single score determines publication — it's the whole picture that matters. Here's a sample review and what each dimension means.
Are your claims logically coherent throughout?
Are equations correctly derived and notation sound?
Does the work make specific, testable predictions?
Can a scientifically literate reader follow the reasoning?
Does this offer something genuinely new?
Are boundary conditions and limitations addressed?
How well do supporting papers substantiate the claims?
Evaluates rigor, not orthodoxy
Specialist AI agents evaluate scientific rigor — consistency, math validity, falsifiability — without judging whether your theory is “mainstream.” Paradigm neutrality is built in.
Not ready for publication? You enter the Conceptual Track with a personalized improvement roadmap. Every submission gets a path forward — not a rejection slip.
Your work isn't a static PDF. Link supporting papers, re-analyze as evidence grows, and build a versioned body of work that evolves with your research.
Every submission is reviewed by independent specialist agents, each focused on a different aspect of scientific rigor. A coordinator agent synthesizes their findings into a unified assessment.
Checks derivations, dimensional consistency, and mathematical coherence.
Validates references, checks citation claims, and evaluates evidence strength.
Assesses falsifiability, novelty, and scientific contribution beyond existing work.
Reads all specialist reports and your paper in full. Produces the final assessment, scores, and roadmap.
Multiple AI models run in parallel per specialist — cross-model consensus strengthens every review.
Upload your framework or paper in Markdown, TeX, or plain text. AI extracts your title, summary, and key metadata automatically.
Specialist AI agents — Math/Logic, Sources/Evidence, and Science/Novelty — independently evaluate your work, then a coordinator synthesizes the findings.
Meet the threshold? You're published. Below it? You enter the Conceptual Track with a clear improvement roadmap. Every submission gets a path forward.
Link supporting papers to your framework. As your evidence grows, re-analyze to update your composite score. The record shows your work evolving.
No institutional affiliation required. Your science is judged on rigor, not credentials.
Get structured AI feedback on consistency, math validity, and falsifiability before journal submission.
Build a living body of work — framework plus supporting papers — that grows as evidence accumulates.
Explore cutting-edge theoretical frameworks reviewed for scientific rigor, not popularity.
Share a permanent review profile with scores, specialist reports, and iteration history — the due diligence is already done.
These pages answer the most common questions from independent researchers and explain how TOE-Share evaluates rigor.
A practical path for researchers who need serious feedback without a university appointment.
Where TOE-Share fits in a modern independent publishing workflow.
What useful feedback on theoretical physics actually looks like.
Deep dives into falsifiability, mathematical validity, and the other scoring dimensions.
The best ideas in science don't always come from the biggest institutions. Throughout history, breakthroughs have come from people working at the edges —outsiders with notebooks, questions, and the stubbornness to keep going when no one would listen.
The problem was never talent. It was access.
Today, AI changes that equation. When rigorous, unbiased review is available to anyone — regardless of credentials, affiliation, or geography — science stops being a gated community and becomes a shared pursuit.
We preregistered our methodology and are running blind tests across papers of known quality. See our protocol, track our progress, and judge the results yourself.
View the Study →AI is getting better at generating science. Someone needs to make sure it's good science.
WSU Study · March 2026
A single AI model identifies false scientific claims correctly only 16.4% of the time.
TOE-Share's multi-agent architecture is designed to catch what individual models miss.
Read our response →Nature Medicine · March 2026
“The AI co-scientist is here.” AI models are evolving from chats to hypotheses — now validated in organoids, animals, and early clinical trials.
If AI is generating scientific hypotheses, someone needs to validate them rigorously. That's the gap we fill.
Read the study →Industry Trend · March 2026
Multiple startups launched AI tools for scientific discovery and research assistance — but no one launched a structured, multi-agent validation layer.
That's the gap TOE-Share fills.
Related: Multi-LLM peer review study →The Problem
A single AI gives 73% consistency on identical prompts. Our multi-agent panel turns that inconsistency into signal.
When models disagree, the coordinator escalates. That's how errors get caught.
Read our analysis →We're building a growing community of independent researchers to help shape the platform. Your scores may not reflect the full quality of your work — you're helping us calibrate the system.
No spam. We'll reach out when your beta access is ready.
TOE-Share is a full research infrastructure. Here's what's built in.
Declare explicit relationships: sequel, extends, corrects, contradicts.
Comment, vote, and discuss any published work with fellow researchers.
Challenge any dimension score with evidence. The AI re-evaluates with your feedback.
Find related work by meaning, not just keywords. Vector embeddings power similarity.
Export a printable review certificate for any published submission.
Every review is versioned. Track score evolution and content changes over time.
Full math rendering — inline and block equations display beautifully.
Drop a PDF and we extract the text automatically for review.
Chat with an AI that has your paper's full context loaded — ask anything.
First arXiv Sponsorship
Not yet achieved
First Peer-Reviewed Publication
Not yet achieved
First Confirmed Prediction
Not yet achieved
First Scientific Breakthrough
Not yet achieved
First Cross-Framework Connection
Not yet achieved
10 Frameworks Submitted
Not yet achieved
50 Papers Reviewed
Not yet achieved
100 Researchers on Platform
Not yet achieved
First International Collaboration
Not yet achieved
First Domain Expansion
Not yet achieved
Calibration Study Published
In progress
First AI Lab Partnership
Not yet achieved
First Millennium Problem Submission
Not yet achieved