# Stability Mechanisms

The Clarus Clinical Stability Benchmark organizes datasets according to two dimensions:

1. **Instability mechanism**  
2. **System domain**

Each dataset represents a specific combination of these two dimensions.

This structure ensures the benchmark grows in a coherent way rather than as a collection of unrelated datasets.

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# Instability Mechanisms

These mechanisms describe the underlying dynamics that cause systems to become unstable.

## Pressure Overload

Demand exceeds system capacity.

Examples:
- circulatory overload
- hospital workload spikes
- metabolic demand surges

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## Buffer Exhaustion

Protective reserves are depleted.

Examples:
- renal buffering failure
- endocrine metabolic exhaustion
- coagulation reserve collapse

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## Coupling Cascade

Multiple subsystems begin amplifying each other’s failures.

Examples:
- organ coupling cascades
- inflammatory cascades
- metabolic feedback loops

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## Delay Instability

The system response occurs too late to restore stability.

Examples:
- delayed antibiotic treatment
- delayed hemorrhage control
- delayed ventilation support

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## Control Loop Failure

Regulatory feedback mechanisms stop stabilizing the system.

Examples:
- respiratory drive failure
- autonomic instability
- thermoregulation breakdown

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## Recovery Window Closure

A system may be recoverable early but becomes unrecoverable once a stability threshold is crossed.

Examples:
- hemorrhage compensation collapse
- sepsis recovery window loss
- cardiac arrest progression

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# System Domains

Instability mechanisms can occur in different physiological or operational systems.

Examples of domains included in the benchmark:

- circulation
- microcirculation
- cellular energy metabolism
- respiratory regulation
- endocrine regulation
- thermoregulation
- coagulation
- electrolyte balance
- hospital operational systems

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# Dataset Design Rule

Each dataset in the Clarus benchmark represents:
instability mechanism + system domain


Example:

| 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

New datasets should follow this rule.

When expanding the benchmark:

1. Choose a stability mechanism
2. Choose a system domain
3. Design variables that represent that regime

This ensures the benchmark remains structured while allowing the dataset suite to grow over time.