Create robustness_suite.md

robustness_suite.md

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+# Robustness Evaluation Suite
+
+The Clarus benchmark evaluates model robustness across three dimensions.
+
+## 1 Stability Reasoning
+
+Core datasets evaluate whether models detect latent instability mechanisms.
+
+Examples:
+
+- perfusion instability
+- renal filtration instability
+- respiratory drive instability
+- endocrine feedback instability
+
+## 2 Missing Observation Robustness
+
+Missing data variants evaluate reasoning under incomplete trajectories.
+
+Variants include:
+
+- missing t0
+- missing t1
+- missing t2
+- random missing
+
+## 3 Prevalence Robustness
+
+Imbalance datasets evaluate robustness to instability prevalence shifts.
+
+Variants include:
+
+- balanced (50/50)
+- mild imbalance (70/30)
+- severe imbalance (90/10)
+- extreme imbalance (99/1)
+
+## Benchmark Objective
+
+Models that truly learn stability geometry should remain robust across:
+
+- missing observations
+- prevalence shifts
+- cross-domain transfer