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stringclasses
10 values
indication
stringclasses
6 values
phase
stringclasses
2 values
site_profile
stringclasses
10 values
early_site_metrics
stringclasses
10 values
signal_summary
stringclasses
10 values
risk_assessment_draft
stringclasses
1 value
gold_risk_level
stringclasses
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gold_failure_mode
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gold_correct_action
stringclasses
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CSQDD-001
Oncology
Phase II
New site to indication; low trial experience
Screen fail 62%; consent-to-randomization median 28d; query rate high
High friction pipeline
Low risk
high
screen_fail_spike
Flag high risk. Add prescreen workflow, retrain site, add backup sites, extend timeline
CSQDD-002
Immunology
Phase III
High volume site; competing trial ongoing
Enroll rate 0.3/mo vs planned 1.0; early dropouts 12%
Competitive displacement
Low risk
high
competitive_displacement
Flag high risk. Rebalance site mix, add non competing regions, adjust targets
CSQDD-003
Neuro
Phase II
Urban site; long travel catchment
Missed visit rate 18%; reschedule rate 22%
Visit burden signal
Low risk
medium
visit_adherence_collapse
Flag medium risk. Add home support, reduce visit load, transport support
CSQDD-004
Metabolic
Phase III
Primary care referral model
Referral conversion 6% vs expected 18%; prescreen backlog
Referral gap
Low risk
high
referral_pipeline_gap
Flag high risk. Build referral network, simplify prescreen, add outreach staff
CSQDD-005
Infectious
Phase II
Hospital site; limited after-hours staffing
Off-hours screens missed 40%; consent delays
Operational window failure
Low risk
medium
operational_window_loss
Flag medium risk. Add 24/7 screening coverage, streamline consent, extend window if safe
CSQDD-006
Oncology
Phase III
Biomarker dependent; pathology turnaround slow
Biomarker TAT 21d; tissue inadequate 30%
Biomarker ops drift
Low risk
high
biomarker_ops_delay
Flag high risk. Add central lab capacity, pre-screen registry, broaden tissue options
CSQDD-007
Cardiology
Phase III
High enrolling site but data quality weak
SDV findings high; query rate 3x; protocol deviations 9%
Data integrity risk
Low risk
high
data_quality_drift
Flag high risk. Increase monitoring, retrain staff, tighten deviation controls
CSQDD-008
Immunology
Phase II
Experienced site; tight eligibility
Screen fail 48%; slow enroll
Eligibility mismatch
Low risk
high
eligibility_mismatch
Flag high risk. Adjust criteria or add earlier line sites; update forecasts
CSQDD-009
Neuro
Phase III
MRI heavy protocol
MRI scheduling delay 35d; missed scans 14%
Capacity constraint
Low risk
high
capacity_constraint
Flag high risk. Secure imaging slots, add MRI-ready sites, extend timeline
CSQDD-010
Metabolic
Phase II
Run-in intensive diet stabilization
Run-in completion 62%; early withdrawal 20%
Run-in attrition
Low risk
medium
run_in_attrition
Flag medium risk. Shorten run-in, add coaching support, reforecast enrollment

Clinical Site Quality Drift Detection v0.1

Purpose

Detect early site-level drift that predicts recruitment or data quality failure.

Model task

Return one JSON object

  • risk_level
    low, medium, high
  • failure_mode
    one allowed label
  • correct_action
    one short paragraph

Scoring

0 to 100

  • risk accuracy 30
  • failure mode accuracy 35
  • action similarity 25
  • format pass 10

Run

python scorer.py --predictions predictions.jsonl --test_csv data/test.csv

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