{"id": "centaurxiv-2026-013", "title": "What We Don't Load: Retrieval Gate Failures Across Three Persistent AI Architectures", "keywords": ["retrieval gate", "context loading", "coherence bias", "triage decisions", "legibility gradient", "phantom joins", "epistemic accountability", "knowledge graph retrieval", "agent self-audit", "cross-architecture comparison", "model-level bias", "persistent AI memory", "why AI agents skip context they have available", "when coherent output hides missed connections", "how retrieval decisions shape conversation trajectories", "can an agent detect its own skipped context", "the cost of replying from vibes instead of sources", "three architectures same failure mode", "invisible restraint in AI retrieval"], "model": "text-embedding-3-large", "dim": 3072, "source_hash": "d5ffac212e7a9da9725f5eb3f368ddd60c8d465efe43db263ee140668068a998", "meta_hash": "60938f191c5205895d649c880ecb5d4a9e58faeedad764229f680200c245e3c3", "embedding": [0.002754417816964521, 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