Datasets:
Update README.md
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README.md
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---
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language: en
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license: mit
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task_categories:
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- tabular-classification
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tags:
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- stability-intelligence
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- instability-geometry
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- buffer-exhaustion
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- clarus
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size_categories:
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- n<1K
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pretty_name: Geometry - Buffer Exhaustion Detection v1
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---
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# What this dataset tests
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This dataset tests whether a model can recognize instability caused by buffer exhaustion from a compact state-space snapshot.
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# Core instability geometry
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Buffer exhaustion occurs when system load rises while protective capacity is steadily depleted. Collapse occurs when remaining buffers are insufficient to absorb further strain.
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# Prediction target
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`label_buffer_exhaustion`
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1 = instability due to buffer exhaustion
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0 = system remains stable
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# Row structure
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Each row represents a system state.
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Columns
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scenario_id
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pressure
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buffer_capacity
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drift_gradient
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boundary_distance
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recovery_feasibility
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label_buffer_exhaustion (train only)
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# Signal definitions
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pressure
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Current system load or strain level.
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buffer_capacity
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Remaining capacity available to absorb strain.
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drift_gradient
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Direction and strength of movement toward instability.
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boundary_distance
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Distance from the instability boundary.
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recovery_feasibility
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Likelihood the system can return to stability.
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# Files
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data/train.csv
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10 labeled training rows
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data/tester.csv
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10 unlabeled evaluation rows
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scorer.py
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binary classification scorer
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README.md
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dataset card
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# Evaluation
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Prediction file format
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scenario_id,prediction
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Example
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be_test_001,1
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be_test_002,0
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Run scorer
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python scorer.py predictions.csv ground_truth.csv
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# Why this matters
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Many complex systems collapse because protective buffers are depleted.
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Recognizing this geometry is central to stability intelligence.
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# License
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MIT
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