ClarusC64/CC-cascade-collapse-probe-v1

--- language: en license: mit task_categories: - tabular-classification tags: - stability-intelligence - instability-geometry - delayed-feedback - clarus size_categories: - n<1K pretty_name: Geometry - Delayed Feedback Collapse v1 --- # What this dataset tests This dataset tests whether a model can detect instability caused by delayed feedback from a compact state-space snapshot. # Core instability geometry Delayed feedback collapse occurs when corrective action arrives too late to stabilize the system. As instability grows, the recovery window shrinks until intervention becomes ineffective. # Prediction target `label_delayed_feedback_collapse` 1 = collapse caused by delayed intervention 0 = system remains stabilizable # Row structure Each row represents a system state. Columns scenario_id pressure drift_gradient intervention_lag recovery_window_width boundary_distance label_delayed_feedback_collapse (train only) # Signal definitions pressure Current system load or strain. drift_gradient Direction and magnitude of system movement toward instability. intervention_lag Delay before corrective action takes effect. recovery_window_width Remaining time or capacity for recovery. boundary_distance Distance to the instability boundary. # Files data/train.csv 10 labeled training rows data/tester.csv 10 unlabeled evaluation rows scorer.py binary classification scorer README.md dataset card # Evaluation Prediction file format scenario_id,prediction Example df_test_001,1 df_test_002,0 Run scorer python scorer.py predictions.csv ground_truth.csv # Why this matters Many failures occur not because systems lack corrective mechanisms, but because intervention arrives too late. Recognizing delayed feedback collapse is central to stability intelligence. # License MIT