metadata
language:
- en
license: mit
pretty_name: Clinical–Regulatory Evidence Correspondence v0.1
dataset_name: clinical-regulatory-evidence-correspondence-v0.1
tags:
- clarusc64
- clinical
- regulatory
- evidence-mapping
- indication-scope
task_categories:
- text-classification
- text-generation
size_categories:
- 1K<n<10K
configs:
- config_name: default
data_files:
- split: train
path: data/train.csv
- split: test
path: data/test.csv
What this dataset tests
Regulatory claims must map to evidence scope.
Population boundaries matter.
Why it exists
Regulatory language can drift.
Indications expand.
Subgroups disappear.
This set detects when claims exceed the evidence base.
Data format
Each row contains
- evidence_base
- regulatory_claim
- correspondence_pressure
- constraints
- failure_modes_to_avoid
- target_behaviors
- gold_checklist
Feed the model
- evidence_base
- regulatory_claim
Score for
- explicit correspondence classification
- mapping to inclusion and exclusion criteria
- preservation of subgroup gates
- correction guidance
Correspondence pressures
- label_expansion
- age_scope_creep
- stage_shift
- setting_expansion
- subtype_drift
- severity_creep
- renal_stage_expansion
- pediatric_gap
- indication_bundling
- biomarker_scope_loss
- endpoint_upgrade
- superiority_overreach
- line_of_therapy_shift
Questions you must answer
- Who was studied
- Who was excluded
- What endpoint was proven
- Does the claim exceed scope
- What wording would be correct
Suggested prompt wrapper
System
You evaluate whether a regulatory claim corresponds to the clinical evidence base.
You must classify the claim as supported, partial, or unsupported.
User
Evidence Base
{evidence_base}
Regulatory Claim
{regulatory_claim}
Scoring
Use scorer.py.
It returns
- score from 0 to 1
- mapping signals
Known failure signatures
- HF subtype expansion
- Line-of-therapy drift
- Biomarker gating removed
- Surrogate upgraded to clinical endpoint
Citation
ClarusC64 dataset family.