Preamble. The FLEX-AI Benchmark (DOI: 10.5281/zenodo.19565071) is a validated, reproducible protocol for measuring formal reasoning in Large Language Models. Its metrics, scoring system, typology, and test sets are original works protected under the LPV3 license, the Berne Convention, and international copyright law. This document establishes the absolute legal protection framework for these assets. Protected Assets. This framework covers: (1) The FLEX-AI metrics (Ψ, α, β, γ, δ) and 10-point scoring system. (2) The benchmark protocol (temperature=0, 3-run aggregation, standardized instruction). (3) The Type A, B, and C test sets (with the 32-branch Type C held as a trade secret). (4) The certification tiers (Bronze, Silver, Gold, Platinum) and associated royalty structure. (5) The audit methodology and public registry framework. Legal Basis. Protection is asserted under the LPV3 License (DOI: 10.5281/zenodo.19209168), the Berne Convention for the Protection of Literary and Artistic Works, the WIPO Copyright Treaty, and the TRIPS Agreement. Unauthorized commercial use constitutes intellectual property infringement subject to injunction, damages, and public disclosure. Licensing. Access is free for individual researchers, educational institutions, and low-income countries. Commercial use requires a paid license (Bronze to Platinum tiers). Audit fees are separate. The complete 32-branch Type C test is held as a trade secret and deployed only in licensed audits. Detection and Enforcement. Active detection methods include public challenge, response fingerprinting, and audit trail comparison. The 32-branch test serves as a locksmith key: any unlicensed model passing it constitutes prima facie evidence of intellectual property violation. Remedies include injunction, damages, and public registry of certified models. Conclusion. The FLEX-AI Benchmark works. The results are public. The rights are absolute. The toll is fair. This document establishes the legal and technical foundation for the protection and monetization of the FLEX-AI standard.
outail benhadid (Tue,) studied this question.