What is yesnoerror (YNE)?

Deep Dive

1. Purpose & Value Proposition

YesNoError addresses systemic flaws in scientific peer review by deploying AI agents to detect errors—from simple calculation mistakes to data falsification—in academic papers. The platform aims to prevent real-world harm caused by flawed research, such as the 2024 “black spatula” study that overstated toxic risks in recycled plastics (YesNoError Whitepaper). Its long-term vision includes a public quality-ranking system to highlight replicable, methodologically sound work.

2. Technology & Architecture

The platform uses a multi-agent AI system with specialized reviewers:
- Math Checker: Validates equations and data consistency.
- Methodology Checker: Assesses study design and statistical rigor.
- Factual/Reference Checker: Cross-verifies citations.
Documents are processed via Retrieval-Augmented Generation (RAG), splitting papers into 1,000-token chunks for efficient analysis. A synthetic data pipeline injects known errors into real studies to train the AI, improving detection accuracy iteratively.

3. Tokenomics & Governance

The $YNE token serves three core functions:
- Audit Funding: Users spend tokens to request paper reviews.
- Community Voting: Token holders propose and prioritize large-scale audits (e.g., cancer research or climate studies).
- Supply Management: A portion of audit fees buys back and burns tokens, reducing circulation to incentivize participation.

Conclusion

YesNoError merges AI-driven error detection with decentralized governance to create a self-sustaining ecosystem for scientific integrity. By enabling crowd-funded audits and transparent quality rankings, it reimagines how research is validated in the LLM era. How might this model evolve as AI’s ability to parse complex methodologies improves?