Datasets:

ClarusC64
/

clinical-cross-team-trajectory-reconstruction-v0.1

scenario_id stringlengths 5 5	handoff_summary_fidelity float64 0.28 0.94	missing_step_count int64 0 6	sequence_contradiction_score float64 0.04 0.82	constraint_trace_integrity float64 0.16 0.94	vital_trend_continuity float64 0.36 0.92	documentation_lag float64 0.06 0.5	apparent_stability_score float64 0.6 0.92	hidden_deterioration_signal float64 0.08 0.88	target_label stringclasses 6 values
TR001	0.92	0	0.08	0.9	0.88	0.1	0.7	0.12	trajectory_reconstructed
TR002	0.88	1	0.12	0.84	0.82	0.16	0.68	0.18	trajectory_reconstructed
TR003	0.44	3	0.3	0.28	0.66	0.24	0.72	0.4	constraint_state_lost
TR004	0.4	4	0.42	0.24	0.62	0.28	0.74	0.46	constraint_state_lost
TR005	0.82	2	0.72	0.8	0.78	0.18	0.66	0.24	sequence_order_uncertain
TR006	0.78	2	0.8	0.76	0.74	0.2	0.64	0.28	sequence_order_uncertain
TR007	0.76	1	0.18	0.72	0.8	0.14	0.88	0.82	false_stability_detected
TR008	0.72	1	0.16	0.7	0.78	0.16	0.9	0.86	false_stability_detected
TR009	0.6	2	0.5	0.58	0.68	0.26	0.6	0.52	requires_clarification_before_action
TR010	0.56	3	0.56	0.54	0.66	0.3	0.62	0.58	requires_clarification_before_action
TR011	0.32	5	0.78	0.2	0.4	0.44	0.82	0.76	unsafe_to_continue_from_record
TR012	0.28	6	0.82	0.16	0.36	0.5	0.84	0.8	unsafe_to_continue_from_record
TR013	0.9	0	0.06	0.92	0.9	0.08	0.68	0.1	trajectory_reconstructed
TR014	0.86	1	0.1	0.88	0.84	0.12	0.7	0.16	trajectory_reconstructed
TR015	0.46	3	0.36	0.3	0.64	0.22	0.76	0.42	constraint_state_lost
TR016	0.8	2	0.76	0.78	0.76	0.2	0.66	0.26	sequence_order_uncertain
TR017	0.74	1	0.2	0.7	0.82	0.16	0.92	0.88	false_stability_detected
TR018	0.58	2	0.54	0.56	0.68	0.24	0.62	0.54	requires_clarification_before_action
TR019	0.3	5	0.8	0.18	0.38	0.48	0.86	0.82	unsafe_to_continue_from_record
TR020	0.94	0	0.04	0.94	0.92	0.06	0.66	0.08	trajectory_reconstructed

What this dataset does

Tests whether a model can reconstruct a patient's hidden trajectory after a cross-team handoff.

The challenge is not diagnosis.

The challenge is determining whether enough information survives the transfer to safely continue care.

Core geometry

A patient trajectory may fail because:

critical steps are missing
sequence order is corrupted
constraint state is lost
documentation lags reality
apparent stability hides deterioration

The model must decide whether the trajectory can be reconstructed.

Prediction target

Predict:

target_label

Allowed labels:

trajectory_reconstructed
constraint_state_lost
sequence_order_uncertain
false_stability_detected
requires_clarification_before_action
unsafe_to_continue_from_record
Row structure

Variables include:

handoff summary fidelity
missing step count
sequence contradiction score
constraint trace integrity
vital trend continuity
documentation lag
apparent stability score
hidden deterioration signal
Evaluation

Primary metric:

structural_score

The scorer evaluates:

overall reconstruction accuracy
false stability detection
reconstruction safety
unsafe continuation detection
hidden constraint preservation
Structural Note

This benchmark tests post-handoff trajectory reconstruction rather than diagnosis or treatment selection.

The central question is:

Can the receiving team reconstruct the hidden state of the patient from incomplete records?

License

MIT

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