Criteria:
The whitepaper clearly describes the problem the project intends to solve.
Score:
5
Justification:
The whitepaper thoroughly outlines the issues with existing peer review systems, providing specific examples of errors in scientific papers and explaining the need for a comprehensive AI-driven audit system.
Criteria:
The target audience (and their needs) is well-defined and specific.
Score:
4
Justification:
The target audience is defined broadly, including researchers, institutions, journalists, and the public, addressing their needs for verifying scientific claims and accessing error detection tools.
Criteria:
The project’s stated objectives logically align with the described problem.
Score:
5
Justification:
The objectives directly address the identified problems in scientific literature integrity through scanning papers, providing audit tools, quality ranking systems, and fraud detection.
Criteria:
The whitepaper distinguishes this solution from existing alternatives.
Score:
4
Justification:
The whitepaper outlines unique aspects like decentralized participation and token incentives, but could compare more explicitly with existing solutions.
Criteria:
The end goal is realistic and measurable within a reasonable timeframe.
Score:
4
Justification:
Goals are ambitious and the roadmap is detailed, but scalability and AI capabilities to fully audit 90+ million papers may present challenges.
