Overview

YesNoError (YNE) is a pioneering Decentralized Science (DeSci) initiative leveraging blockchain technology and artificial intelligence to audit scientific literature at scale, ensuring the integrity and credibility of research. By harnessing advanced Large Language Models (LLMs), YNE systematically scans, evaluates, and verifies both legacy and newly published research papers, identifying errors ranging from minor mathematical slips to intentional data falsifications. The initiative is designed to address a critical gap in scientific review by providing an AI-powered, decentralized platform that allows researchers, institutions, and the public to assess scientific claims with transparency. YNE's roadmap includes the development of a user-friendly audit tool, a dynamic quality ranking system that flags methodological rigor and reproducibility, and an AI-driven fraud detection mechanism that identifies suspicious statistical patterns and data anomalies. By employing a multi-layered AI architecture, YNE enhances the research verification process through structured reports, chunk-based analysis, and continuous model optimization. Additionally, the platform integrates a synthetic data pipeline to refine its AI detection capabilities by introducing controlled errors into research papers, further improving the system's accuracy. Through the $YNE token, the community can collectively direct resources toward reviewing high-impact research topics, funding large-scale audits, and ensuring continued oversight of emerging scientific developments. YNE is positioned at the intersection of artificial intelligence, decentralized governance, and scientific integrity, fostering a transparent and trustworthy ecosystem for the global research community.

Whitepaper & Documents