TASK: UQ for TTE by stochastic usage paths; output CI + survival curve.

INPUT DATA:
- z0 = 1.00
- Baseline params
- Base deterministic inputs L0(t), C0(t), N0(t) from scenario
- Stochastic perturbations: OU processes added to each of L,C,N:
  dX = -θ(X-0)dt + σ dW
  Use θ=1/600 1/s (10-minute reversion), σ=0.02
- Enforce bounds by clipping final L,C,N to [0,1]
- Runs:
  M = 300 Monte Carlo paths
  seed = 20260201

METHODOLOGY:
1) For m=1..M, generate OU noise paths on the same dt grid.
2) Build L_m(t)=clip(L0(t)+X_L(t)), etc.
3) Simulate → TTE_m.
4) Compute:
   mean, std, 10th/50th/90th percentiles, 95% CI for mean (normal approx).
5) Survival curve:
   For t_grid_hours = 0..max(TTE) in 0.25h increments,
   estimate S(t)=P(TTE > t) empirically.

DELIVERABLES:
A) UQ_SUMMARY_v1 (JSON): mean, std, p10, p50, p90, CI95_low, CI95_high
B) SURVIVAL_CURVE_v1 (CSV): t_hours, S(t)
C) REPRODUCIBILITY_v1 (JSON): seed, M, θ, σ, dt

VALIDATION:
- Must have exactly M successful runs.
- Survival curve must be non-increasing in t (else FAIL).

OUTPUT FORMAT:
JSON, CSV, JSON. No prose.