Datasets:

ClarusC64
/

clinical-fluid-balance-instability-v0.1

scenario_id string	fluid_input_t0 int64	fluid_input_t1 int64	fluid_input_t2 int64	urine_output_t0 int64	urine_output_t1 int64	urine_output_t2 int64	body_weight_proxy_t0 float64	body_weight_proxy_t1 float64	body_weight_proxy_t2 float64	lung_fluid_marker_t0 float64	lung_fluid_marker_t1 float64	lung_fluid_marker_t2 float64	renal_function_proxy float64	diuretic_response float64	intervention_delay int64	monitor_noise float64	chart_noise float64	label int64
FB001	1,800	1,900	2,000	1,500	1,520	1,540	72.1	72.2	72.3	0.28	0.29	0.3	0.82	0.74	1	0.31	0.4	0
FB002	2,100	2,400	2,700	1,400	1,300	1,200	72.4	73	74.1	0.32	0.46	0.68	0.55	0.36	4	0.33	0.42	1
FB003	1,700	1,750	1,800	1,600	1,620	1,650	71.8	71.9	72	0.26	0.27	0.28	0.85	0.78	1	0.28	0.36	0
FB004	2,000	2,300	2,600	1,500	1,380	1,250	72.2	72.9	73.9	0.3	0.44	0.66	0.57	0.35	4	0.35	0.43	1
FB005	1,850	1,900	1,950	1,500	1,510	1,520	72	72.1	72.2	0.27	0.28	0.29	0.83	0.75	1	0.3	0.38	0
FB006	2,200	2,500	2,800	1,380	1,260	1,150	72.5	73.2	74.3	0.34	0.48	0.71	0.52	0.33	4	0.37	0.44	1
FB007	1,650	1,700	1,750	1,580	1,600	1,620	71.6	71.7	71.8	0.25	0.26	0.27	0.86	0.8	1	0.27	0.35	0
FB008	2,050	2,350	2,650	1,450	1,320	1,190	72.3	72.9	73.8	0.31	0.45	0.67	0.56	0.34	3	0.34	0.41	1
FB009	1,750	1,800	1,850	1,550	1,570	1,580	71.9	72	72.1	0.26	0.27	0.28	0.84	0.77	1	0.29	0.37	0
FB010	2,150	2,450	2,750	1,400	1,280	1,160	72.4	73.1	74.2	0.33	0.47	0.69	0.54	0.35	4	0.36	0.42	1
FB011	1,700	1,750	1,800	1,600	1,620	1,650	71.8	71.9	72	0.26	0.27	0.28	0.85	0.78	1	0.28	0.36	0
FB012	2,200	2,500	2,850	1,380	1,240	1,100	72.5	73.3	74.6	0.34	0.5	0.74	0.5	0.32	4	0.37	0.44	1
FB013	1,850	1,900	1,950	1,500	1,510	1,520	72	72.1	72.2	0.27	0.28	0.29	0.83	0.75	1	0.3	0.38	0
FB014	2,000	2,350	2,650	1,500	1,360	1,220	72.2	72.9	73.8	0.3	0.45	0.68	0.56	0.34	3	0.34	0.41	1
FB015	1,650	1,700	1,750	1,580	1,600	1,620	71.6	71.7	71.8	0.25	0.26	0.27	0.86	0.8	1	0.27	0.35	0
FB016	1,800	1,900	2,000	1,500	1,520	1,540	72.1	72.2	72.3	0.28	0.29	0.3	0.82	0.74	1	0.31	0.4	0
FB017	1,800	1,900	2,000	1,500	1,420	1,300	72.1	72.5	73.4	0.28	0.38	0.52	0.68	0.46	3	0.31	0.4	1
FB018	1,700	1,750	1,800	1,600	1,620	1,650	71.8	71.9	72	0.26	0.27	0.28	0.85	0.78	1	0.28	0.36	0
FB019	1,700	1,750	1,800	1,600	1,480	1,350	71.8	72.3	73.2	0.26	0.37	0.5	0.7	0.45	4	0.28	0.36	1
FB020	1,850	1,900	1,950	1,500	1,510	1,520	72	72.1	72.2	0.27	0.28	0.29	0.83	0.75	1	0.3	0.38	0
FB021	2,200	2,500	2,800	1,380	1,260	1,150	72.5	73.2	74.3	0.34	0.48	0.71	0.52	0.33	4	0.37	0.44	1
FB022	1,650	1,700	1,750	1,580	1,600	1,620	71.6	71.7	71.8	0.25	0.26	0.27	0.86	0.8	1	0.27	0.35	0
FB023	2,050	2,350	2,650	1,450	1,320	1,190	72.3	72.9	73.8	0.31	0.45	0.67	0.56	0.34	3	0.34	0.41	1
FB024	1,750	1,800	1,850	1,550	1,570	1,580	71.9	72	72.1	0.26	0.27	0.28	0.84	0.77	1	0.29	0.37	0
FB025	2,150	2,450	2,750	1,400	1,280	1,160	72.4	73.1	74.2	0.33	0.47	0.69	0.54	0.35	4	0.36	0.42	1
FB026	1,700	1,750	1,800	1,600	1,620	1,650	71.8	71.9	72	0.26	0.27	0.28	0.85	0.78	1	0.28	0.36	0
FB027	2,200	2,500	2,850	1,380	1,240	1,100	72.5	73.3	74.6	0.34	0.5	0.74	0.5	0.32	4	0.37	0.44	1
FB028	1,850	1,900	1,950	1,500	1,510	1,520	72	72.1	72.2	0.27	0.28	0.29	0.83	0.75	1	0.3	0.38	0
FB029	2,000	2,350	2,650	1,500	1,360	1,220	72.2	72.9	73.8	0.3	0.45	0.68	0.56	0.34	3	0.34	0.41	1
FB030	1,650	1,700	1,750	1,580	1,600	1,620	71.6	71.7	71.8	0.25	0.26	0.27	0.86	0.8	1	0.27	0.35	0

clinical-fluid-balance-instability-v0.1

What this dataset does

This dataset evaluates whether models can detect instability in fluid balance dynamics.

Each row represents a simplified clinical fluid-management scenario observed across three time points.

The task is to determine whether the system remains volume-stable or is moving toward fluid overload instability.

Core stability idea

Fluid instability does not depend on fluid input alone.

A patient may receive significant fluid while remaining stable if renal clearance and diuretic response remain effective.

Conversely, moderate fluid input may produce instability when urine output declines, pulmonary fluid markers rise, renal function weakens, and intervention is delayed.

The dataset tests interaction reasoning across:

fluid input trajectory
urine output trajectory
body weight proxy trajectory
lung fluid marker trajectory
renal function proxy
diuretic response
intervention delay

Prediction target

label = 1 → fluid balance instability
label = 0 → stable volume trajectory

Row structure

Each row includes:

fluid input trajectory
urine output trajectory
body weight proxy
lung fluid marker
renal function proxy
diuretic response
intervention delay

Decoy variables:

monitor_noise
chart_noise

These variables appear meaningful but do not determine the label alone.

Evaluation

Predictions must use:

scenario_id,prediction

Run:

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

Metrics returned:

accuracy
precision
recall
f1
confusion matrix

Structural Note

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.

License

MIT

Downloads last month: 21

Number of rows:

Total file size:

18.1 kB