| # Stability Mechanisms |
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| The Clarus Clinical Stability Benchmark organizes datasets according to two dimensions: |
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| 1. **Instability mechanism** |
| 2. **System domain** |
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| Each dataset represents a specific combination of these two dimensions. |
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| This structure ensures the benchmark grows in a coherent way rather than as a collection of unrelated datasets. |
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| # Instability Mechanisms |
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| These mechanisms describe the underlying dynamics that cause systems to become unstable. |
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| ## Pressure Overload |
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| Demand exceeds system capacity. |
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| Examples: |
| - circulatory overload |
| - hospital workload spikes |
| - metabolic demand surges |
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| ## Buffer Exhaustion |
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| Protective reserves are depleted. |
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| Examples: |
| - renal buffering failure |
| - endocrine metabolic exhaustion |
| - coagulation reserve collapse |
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| ## Coupling Cascade |
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| Multiple subsystems begin amplifying each other’s failures. |
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| Examples: |
| - organ coupling cascades |
| - inflammatory cascades |
| - metabolic feedback loops |
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| ## Delay Instability |
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| The system response occurs too late to restore stability. |
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| Examples: |
| - delayed antibiotic treatment |
| - delayed hemorrhage control |
| - delayed ventilation support |
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| ## Control Loop Failure |
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| Regulatory feedback mechanisms stop stabilizing the system. |
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| Examples: |
| - respiratory drive failure |
| - autonomic instability |
| - thermoregulation breakdown |
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| ## Recovery Window Closure |
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| A system may be recoverable early but becomes unrecoverable once a stability threshold is crossed. |
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| Examples: |
| - hemorrhage compensation collapse |
| - sepsis recovery window loss |
| - cardiac arrest progression |
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| # System Domains |
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| Instability mechanisms can occur in different physiological or operational systems. |
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| Examples of domains included in the benchmark: |
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| - circulation |
| - microcirculation |
| - cellular energy metabolism |
| - respiratory regulation |
| - endocrine regulation |
| - thermoregulation |
| - coagulation |
| - electrolyte balance |
| - hospital operational systems |
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| # Dataset Design Rule |
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| Each dataset in the Clarus benchmark represents: |
| instability mechanism + system domain |
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| Example: |
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| | Mechanism | Domain | Dataset | |
| |---|---|---| |
| | Pressure overload | circulation | clinical-hemodynamic-collapse | |
| | Buffer exhaustion | metabolism | clinical-endocrine-instability | |
| | Coupling cascade | organs | clinical-organ-coupling-cascade | |
| | Delay instability | treatment | clinical-intervention-delay-failure | |
| | Control loop failure | respiration | clinical-respiratory-drive-instability | |
| | Recovery window closure | trauma | clinical-hemorrhage-compensation-collapse | |
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| # Benchmark Expansion |
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| New datasets should follow this rule. |
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| When expanding the benchmark: |
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| 1. Choose a stability mechanism |
| 2. Choose a system domain |
| 3. Design variables that represent that regime |
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| This ensures the benchmark remains structured while allowing the dataset suite to grow over time. |
