yesnoerrorPrice

(YNE)

YNE serves as the utility and governance token for the platform. It is primarily used to fund priority audits for scientific research papers. Token holders can use YNE to request that the AI engine—powered by advanced models like OpenAI’s o1—prioritize specific papers for error detection. Additionally, YNE is used to reward contributors who assist in the auditing process and allows holders to participate in community-driven governance, helping to prioritize which areas of research the platform should focus on next.

The project utilizes a multi-agent AI framework to scan scientific documents for mathematical errors, data inconsistencies, and issues like "p-hacking." Rather than replacing human experts, the AI is designed to complement them. It excels at identifying low-level numerical errors and fraudulent patterns within massive documents that human reviewers might overlook, thereby enhancing the overall integrity and speed of scientific validation.

The project was founded by Matt Schlicht and has gained significant attention in the Decentralized Science (DeSci) space. It has received backing and promotion from prominent industry figures such as Andrew Kang of Mechanism Capital. Furthermore, the project has drawn interest from leaders at major AI organizations, including individuals associated with Anthropic and Google DeepMind, signaling strong cross-industry support for its mission to improve scientific accuracy.

The total supply of YNE is approximately 1 billion tokens, with the majority of the supply currently in circulation. To support the token's long-term ecosystem health, the project incorporates a deflationary mechanism. A portion of the revenue generated from platform-led audit services and community-driven prioritization requests is used to buy back and burn YNE tokens. This process reduces the total supply over time as platform adoption and auditing activity increase.

YNE primarily operates on the Solana blockchain, utilizing its high-speed infrastructure for efficient transactions. While currently available on major exchanges like LBank, the project’s roadmap includes plans to develop a cross-chain bridge to the Base network by late 2025. This expansion is intended to increase accessibility and interoperability within the broader decentralized science and Ethereum Layer 2 ecosystems.

Integrating blockchain ensures that all audit reports are immutable and timestamped. By recording AI-generated audit results on-chain, the project creates a permanent, transparent record that cannot be altered. This prevents researchers from suppressing unfavorable findings or errors discovered by the AI after the fact. This transparency fosters higher accountability in scientific publishing and ensures that the integrity of research data remains verifiable by the global community.