⚖️
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.
Beta Availability
Beta account capacity is currently full
The beta phase is open. We're accepting 10 new account registrations starting May 5, 2026, then pausing until the next capacity increase. Join the waitlist.
15 claimed, 0 available.
theoryofeverything.ai
Your science,
seen clearly.
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.
As of April 25, 2026 — running the latest models from OpenAI, Anthropic, Google & xAI.
The Iteration Effect
3.4
First review
+0.5
3.9
Latest re-review
Across 13 works with author-initiated re-reviews, scores improved by an average of +0.5 points over 17 re-review attempts. 10 out of 13 works showed improvement.
Average gain per re-review: +0.40 points
5
Frameworks submitted
24
Papers submitted
178
Reviews completed
8
Models in rotation
4
AI providers
What a Review Looks Like
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.
AI Review — Sample FrameworkPublished
Internal Consistency
4/5
Mathematical Validity
5/5
Falsifiability
4/5
Clarity
3/5
Novelty
4/5
Completeness
3/5
Evidence Strength
4/5
🔗
Internal Consistency
Are your claims logically coherent throughout?
∑
Mathematical Validity
Are equations correctly derived and notation sound?
🎯
Falsifiability
Does the work make specific, testable predictions?
💡
Clarity
Can a scientifically literate reader follow the reasoning?
✨
Novelty
Does this offer something genuinely new?
📐
Completeness
Are boundary conditions and limitations addressed?
📊
Evidence Strength
How well do supporting papers substantiate the claims?
Built on Three Principles
🛤️
No Dead Ends
Not ready for publication? You enter the Conceptual Track with a personalized improvement roadmap. Every submission gets a path forward — not a rejection slip.
🧬
Living Frameworks
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.
It caught a very specific wording that would have made my paper mathematically invalid. The numbers were right, but one word was wrong.The paper was already with editors at a math journal — I would never have caught it without this.
Not One AI — A Panel of Specialists
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.
∑
Math / Logic Agent
Checks derivations, dimensional consistency, and mathematical coherence.
📚
Sources / Evidence Agent
Validates references, checks citation claims, and evaluates evidence strength.
🔬
Science / Novelty Agent
Assesses falsifiability, novelty, and scientific contribution beyond existing work.
🧠
Coordinator
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.
How It Works
Submit Your Work
Upload your framework or paper in Markdown, TeX, or plain text. AI extracts your title, summary, and key metadata automatically.
Multi-Agent Review
Specialist AI agents — Math/Logic, Sources/Evidence, and Science/Novelty — independently evaluate your work, then a coordinator synthesizes the findings.
Iterate or Publish
Meet the threshold? You're published. Below it? You enter the Conceptual Track with a clear improvement roadmap. Every submission gets a path forward.
Build Your Body of Work
Link supporting papers to your framework. As your evidence grows, re-analyze to update your composite score. The record shows your work evolving.
Who It's For
Independent Researchers
No institutional affiliation required. Your science is judged on rigor, not credentials.
Theoretical Physicists
Get structured AI feedback on consistency, math validity, and falsifiability before journal submission.
Framework Builders
Build a living body of work — framework plus supporting papers — that grows as evidence accumulates.
Science Enthusiasts
Explore cutting-edge theoretical frameworks reviewed for scientific rigor, not popularity.
Endorsement Ready
Share a permanent review profile with scores, specialist reports, and iteration history — the due diligence is already done.
Start with the Right Guide
These pages answer the most common questions from independent researchers and explain how TOE-Share evaluates rigor.
Get Reviewed Without Affiliation
A practical path for researchers who need serious feedback without a university appointment.
Publish as an Independent Researcher
Where TOE-Share fits in a modern independent publishing workflow.
Get Expert Physics Feedback
What useful feedback on theoretical physics actually looks like.
Explore the Rigor Guides
Deep dives into falsifiability, mathematical validity, and the other scoring dimensions.
Our Mission
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.
Why TheoryOfEverything.ai Exists
Why we built this, who it's for, and where it's going. A less than 3-minute introduction to TheoryOfEverything.ai from the person behind it.
Hear It from the Authors
Real researchers. Real frameworks. Watch the people behind the science explain their work in their own words.
Blake Shatto — Mode Identity Theory
Blake Shatto walks through Mode Identity Theory, a framework built from a single topological postulate that claims to derive the cosmological constant, fermion masses, and more across 122 orders of magnitude.
John Holland — General Expanse Tension Theory
John Holland introduces the Gauge-Invariant Singlet Scalar Field, the foundation of his General Expanse Tension Theory, backed by 45 papers on Zenodo. A Chartered Engineer from the UK extending the Standard Model.
Calibration Study Concluded
We tested the review panel before asking researchers to trust it.
The four-phase preregistered study is complete: 70 submissions, 1,965 specialist scores, nine models, repeatability checks, adversarial tests, and one real published-paper error independently identified by the system.
Read the calibration results →70
Submissions
1,965
Scores
9
Models
Why Now
AI is getting better at generating science. Someone needs to make sure it's good science.
Phys.org / APS Survey · May 2026
The largest-ever survey of physicists found that even standard cosmology no longer commands majority support.
Frontier physics is alive because consensus is incomplete. TOE-Share gives non-standard ideas a rigorous way to be tested.
Read the survey coverage →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 →Join the Waitlist
The current account window is full, but the waitlist remains open. Add your email and we'll reach out when more registration slots are available.
No spam. The waitlist is separate from account registration and stays open.
More Than a Review Tool
TOE-Share is a full research infrastructure. Here's what's built in.
Paper-to-Paper Linking
Declare explicit relationships: sequel, extends, corrects, contradicts.
Community Discussion
Comment, vote, and discuss any published work with fellow researchers.
Score Disputes
Challenge any dimension score with evidence. The AI re-evaluates with your feedback.
Semantic Search
Find related work by meaning, not just keywords. Vector embeddings power similarity.
Endorsement Certificates
Export a printable review certificate for any published submission.
Full Review History
Every review is versioned. Track score evolution and content changes over time.
LaTeX & Markdown
Full math rendering — inline and block equations display beautifully.
PDF Upload
Drop a PDF and we extract the text automatically for review.
Ask the AI
Chat with an AI that has your paper's full context loaded — ask anything.
Road Ahead
Scientific Impact
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
Community Growth
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
Platform Quality
Calibration Study Published
Concluded
First AI Lab Partnership
Not yet achieved
First Millennium Problem Submission
Not yet achieved