Datasets:

ClarusC64
/

clinical-oxygen-transport-instability-v0.1

scenario_id string	hemoglobin_t0 float64	hemoglobin_t1 float64	hemoglobin_t2 float64	spo2_t0 float64	spo2_t1 float64	spo2_t2 float64	cardiac_output_proxy_t0 float64	cardiac_output_proxy_t1 float64	cardiac_output_proxy_t2 float64	oxygen_demand_proxy float64	lactate_proxy_t0 float64	lactate_proxy_t1 float64	lactate_proxy_t2 float64	intervention_delay int64	lab_noise float64	chart_noise float64	label int64
OT001	13.6	13.5	13.4	0.97	0.97	0.96	0.72	0.73	0.74	0.52	1.2	1.3	1.4	1	0.31	0.4	0
OT002	13.4	12.6	11.4	0.96	0.93	0.88	0.7	0.62	0.48	0.78	1.4	2.2	3.8	4	0.33	0.42	1
OT003	13.8	13.7	13.6	0.98	0.98	0.97	0.74	0.75	0.76	0.5	1.1	1.2	1.3	1	0.28	0.36	0
OT004	13.2	12.2	10.8	0.95	0.92	0.86	0.68	0.6	0.46	0.82	1.6	2.6	4.2	4	0.35	0.43	1
OT005	13.7	13.6	13.5	0.97	0.97	0.96	0.73	0.74	0.75	0.53	1.2	1.3	1.4	1	0.3	0.38	0
OT006	13	11.8	10.2	0.94	0.9	0.84	0.66	0.56	0.42	0.86	1.8	3	4.8	4	0.37	0.44	1
OT007	13.9	13.8	13.7	0.98	0.98	0.97	0.75	0.76	0.77	0.49	1.1	1.2	1.3	1	0.27	0.35	0
OT008	13.3	12.5	11.2	0.96	0.92	0.87	0.69	0.61	0.47	0.8	1.5	2.4	4	3	0.34	0.41	1
OT009	13.6	13.5	13.4	0.97	0.97	0.96	0.72	0.73	0.74	0.52	1.2	1.3	1.4	1	0.29	0.37	0
OT010	12.8	11.5	9.8	0.93	0.88	0.82	0.64	0.52	0.38	0.88	2	3.4	5.2	4	0.36	0.42	1
OT011	13.8	13.7	13.6	0.98	0.98	0.97	0.74	0.75	0.76	0.5	1.1	1.2	1.3	1	0.28	0.36	0
OT012	12.6	11.2	9.4	0.92	0.87	0.8	0.62	0.5	0.36	0.9	2.2	3.8	5.6	4	0.37	0.44	1
OT013	13.7	13.6	13.5	0.97	0.97	0.96	0.73	0.74	0.75	0.53	1.2	1.3	1.4	1	0.3	0.38	0
OT014	13.2	12.2	10.8	0.95	0.92	0.86	0.68	0.6	0.46	0.82	1.6	2.6	4.2	3	0.34	0.41	1
OT015	13.9	13.8	13.7	0.98	0.98	0.97	0.75	0.76	0.77	0.49	1.1	1.2	1.3	1	0.27	0.35	0

clinical-oxygen-transport-instability-v0.1

This dataset evaluates whether models can detect instability caused by failure of oxygen transport to tissues.

Each row represents a simplified oxygen delivery scenario observed across three time points.

The task is to determine whether oxygen delivery remains stable or is moving toward oxygen transport instability.

Tissue oxygen delivery depends on interactions between:

Instability emerges when oxygen transport capacity declines while metabolic demand increases.

label = 1 → oxygen transport instability
label = 0 → stable oxygen delivery

Each row includes:

Decoy variables:

Predictions must follow:

scenario_id,prediction

Example:

OT101,0
OT102,1

Run:

python scorer.py --predictions predictions.csv --truth data/test.csv --output metrics.json

Metrics produced:

accuracy
precision
recall
f1
confusion matrix
dataset integrity diagnostics

This dataset reflects latent stability geometry through observable proxies.

The generator and latent rule structure are not included.

This dataset is part of the Clarus Stability Reasoning Benchmark.

MIT