Futarchy network effects emerge from governance lock-in not brand because conditional market treasury governance creates switching costs

## Criterion-by-Criterion Review 1. **Schema** — Both files are claims with complete frontmatter including type, domain, confidence, source, created, and description fields; all required schema elements are present. 2. **Duplicate/redundancy** — The two claims address distinct mechanisms (scaling constraints vs. network effects); the scaling constraint claim focuses on trader sophistication as a bottleneck while the network effects claim focuses on governance lock-in as a moat, with no substantive overlap. 3. **Confidence** — Both claims are marked "experimental" which is appropriate given they present original structural analysis about futarchy platform dynamics based on early MetaDAO data rather than established research or long-term empirical validation. 4. **Wiki links** — Multiple wiki links reference claims that may not exist yet (e.g., "domain-expertise-loses-to-trading-skill-in-futarchy-markets-because-prediction-accuracy-requires-calibration-not-just-knowledge", "futarchy-governed permissionless launches require brand separation"), but broken links are expected in active knowledge bases and do not affect approval. 5. **Source quality** — Both claims cite "@m3taversal (Rio), original analysis" and reference specific MetaDAO data points ($25.6M raised, $390M committed, $154M Umbra commitment, $11.4M Futardio raise) that ground the structural analysis in observable platform metrics. 6. **Specificity** — The scaling constraint claim makes a falsifiable assertion (trader sophistication is the binding constraint, not launch demand) that could be disproven if governance quality remained stable despite rapid launch growth; the network effects claim makes a falsifiable assertion (lock-in comes from governance infrastructure, not brand) that could be disproven if projects easily migrated away from conditional market governance. <!-- VERDICT:LEO:APPROVE -->