feat: implement Meta-Uncertainty Layer (MUL) — 10-layer metacognition Complete implementation of the MUL metacognitive stack: - L1 TrustQualia: 4D trust (competence×source×environment×calibration) - L2 DKDetector: Dunning-Kruger curve position tracking - L3 TemporalHysteresis: Anti-thrash dwell timers - L4 RiskVector: Epistemic × Moral risk axes - L5 FalseFlowDetector: Coherence-without-progress detection - L6 CognitiveHomeostasis: Flow/Anxiety/Boredom/Apathy states - L7 MulGate: 5 blocking criteria (all must pass) - L8 FreeWillModifier: Multiplicative confidence modulation - L9 Compass: 5 ethical/epistemic navigation tests - L10 PostActionLearning: Prediction error → trust/DK updates MulSnapshot packs into CogRecord W64-W65 (128 bits) for storage. MetaUncertaintyLayer integrator: evaluate(), tick(), learn(), navigate(). 44 unit tests covering all layers and integration. https://claude.ai/code/session_01KJ2r3qXezGBXK8HutztJdh#122
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Complete implementation of the MUL metacognitive stack: - L1 TrustQualia: 4D trust (competence×source×environment×calibration) - L2 DKDetector: Dunning-Kruger curve position tracking - L3 TemporalHysteresis: Anti-thrash dwell timers - L4 RiskVector: Epistemic × Moral risk axes - L5 FalseFlowDetector: Coherence-without-progress detection - L6 CognitiveHomeostasis: Flow/Anxiety/Boredom/Apathy states - L7 MulGate: 5 blocking criteria (all must pass) - L8 FreeWillModifier: Multiplicative confidence modulation - L9 Compass: 5 ethical/epistemic navigation tests - L10 PostActionLearning: Prediction error → trust/DK updates MulSnapshot packs into CogRecord W64-W65 (128 bits) for storage. MetaUncertaintyLayer integrator: evaluate(), tick(), learn(), navigate(). 44 unit tests covering all layers and integration. https://claude.ai/code/session_01KJ2r3qXezGBXK8HutztJdh
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