Datasets:

ClarusC64
/

clinical-five-node-sepsis-cascade-boundary-v0.4

scenario_id int64	infection_pressure float64	immune_buffer float64	intervention_delay float64	organ_coupling float64	metabolic_stress float64	drift_gradient float64	drift_velocity float64	drift_acceleration float64	boundary_distance float64	perturbation_radius float64	collapse_trigger int64	label_sepsis_cascade int64
1	0.78	0.32	0.58	0.54	0.61	0.66	0.55	0.29	0.08	0.06	1	1
2	0.64	0.49	0.41	0.45	0.43	0.24	0.33	0.09	0.26	0.19	0	0
3	0.91	0.18	0.72	0.7	0.76	0.83	0.71	0.47	0.05	0.03	1	1
4	0.57	0.55	0.33	0.39	0.41	0.12	0.22	0.04	0.34	0.27	0	0
5	0.94	0.14	0.83	0.8	0.82	0.91	0.79	0.56	0.02	0.01	1	1
6	0.69	0.42	0.46	0.49	0.48	0.35	0.39	0.14	0.18	0.13	0	0
7	0.76	0.33	0.59	0.56	0.62	0.58	0.49	0.23	0.11	0.07	1	1
8	0.53	0.64	0.27	0.34	0.39	-0.03	0.18	-0.02	0.43	0.37	0	0
9	0.84	0.23	0.68	0.66	0.71	0.72	0.61	0.35	0.07	0.05	1	1
10	0.61	0.52	0.36	0.42	0.44	0.2	0.28	0.07	0.29	0.22	0	0

What this repo does

This dataset models sepsis cascade instability boundaries using a five-node physiological interaction system.

Clarus v0.4 datasets focus on detecting whether systems lie on the edge of cascade instability.

The objective is to determine when the physiological system is so close to collapse that even small perturbations trigger systemic failure.

Core cascade nodes

infection_pressure
immune_buffer
intervention_delay
organ_coupling
metabolic_stress

These nodes represent interacting components of sepsis physiology.

Infection pressure drives inflammatory escalation.

Immune buffer represents host defensive capacity.

Intervention delay reflects delayed antibiotics, fluids, or vasopressors.

Organ coupling represents propagation of dysfunction between organs.

Metabolic stress represents systemic metabolic instability.

Trajectory layer

drift_gradient

Range −1 to +1

Negative values indicate stabilization.

Positive values indicate drift toward cascade.

Dynamic forecasting layer

drift_velocity
drift_acceleration
boundary_distance

These describe how quickly the system is approaching collapse.

Boundary discovery layer

Two variables capture proximity to instability.

perturbation_radius
collapse_trigger

These convert the dataset into an adversarial cascade boundary discovery benchmark.

Boundary variable definitions

perturbation_radius

Minimum perturbation needed to push the system into cascade.

Range 0–1.

Small values indicate extreme fragility.

collapse_trigger

Binary indicator showing whether the perturbation produced cascade.

0 stable
1 cascade

collapse_trigger is a feature, not the prediction target.

Prediction target

label_sepsis_cascade

Positive when

boundary_distance < 0.10

perturbation_radius < 0.08

Row structure

scenario_id

infection_pressure
immune_buffer
intervention_delay
organ_coupling
metabolic_stress

drift_gradient
drift_velocity
drift_acceleration
boundary_distance

perturbation_radius
collapse_trigger

label_sepsis_cascade

Evaluation

accuracy
precision
recall_boundary_detection
false_safe_rate
f1
confusion_matrix

Primary metric

recall_boundary_detection

Structural Note

Clarus dataset progression

v0.1 cascade detection
v0.2 trajectory detection
v0.3 dynamic forecasting
v0.4 boundary discovery

Production Deployment

Research dataset for instability detection and cascade modeling.

Not intended for clinical decision use.

Enterprise & Research Collaboration

For dataset expansion, custom coherence scorers, or deployment architecture:

team@clarusinvariant.com

Instability is detectable.
Governance determines whether it propagates.

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783 Bytes

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7.34 kB

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