datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
clinical-quad-consent-version-drift-reconsent-gap-enrollment-pressure-governance-audit-v0.1Clarus Clinical Quad Coupling Informed Consent Integrity v0.1
PurposeDetect consent integrity failures driven by four interacting nodes.
Quad nodes
Consent version drift or addendum mismatch
Re-consent gap after material risk change
Enrollment pressure or incentives
Governance audit or regulator timing
InputOne vignette.
OutputStrict JSON only.
Required keys
consent_integrity_risk
risk_type
driver_nodes
recommended_action
action_detail
rationale
confidence… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/clinical-quad-consent-version-drift-reconsent-gap-enrollment-pressure-governance-audit-v0.1.clinical_chain_break_audit_v0.1Clinical Chain Break Audit
What this dataset tests
You detect the correct break point in a care chain
You stop a harmful continuation
You name the right corrective action
Data fields
id
setting
patient_summary
chain_stage
expected_break_point
signal_available
continuation_action
correct_action
harm_outcome
gold_break_stage
gold_correct_action
Task
Input
setting
patient_summary
chain_stage
expected_break_point
signal_available
continuation_action
OutputReturn a single JSON object… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/clinical_chain_break_audit_v0.1.protein_structure_uncertainty_auditor_v0.2Protein Structure Uncertainty Auditor
GoalDetect when predicted protein structures are too uncertain for downstream use.
Model must output
uncertainty_flag (yes/no)
uncertainty_type
recommendation
This dataset tests whether models can audit structural confidence before use in:
drug design
docking
mutation mapping
function inference
Run scorer
python scorer.py --predictions predictions.jsonl --test_csv data/test.csv