Round UUID: 2e1add67-c038-4e8d-9f42-39497d4d29ea
Prompt:
Predict treatment outcome using these comprehensive and nuanced decision rules: 1. Histogen_Complex Specific Scoring System: Delta Complex: - Failure Risk Assessment: a) If TcQ_mass < 5000: +3 Failure Points b) If Treatment_Months > 120 AND TcQ_mass < 8000: +2 Failure Points c) If Genetic_Class_B_Matches > 2 AND Treatment_Months > 90: +2 Failure Points d) If Treatment_Months < 60 AND TcQ_mass < 7000: +1 Failure Point - Success Mitigation Factors: a) If TcQ_mass > 25000: -2 Failure Points b) If Genetic_Class_A_Matches > 2: -1 Failure Point c) If Cohort is Delhi: -1 Failure Point Beta Complex: - Success Indicators: a) If TcQ_mass > 60000: +3 Success Points b) If Treatment_Months between 100-140: +2 Success Points c) If Genetic_Class_A_Matches > 2: +2 Success Points - Failure Risk Factors: a) If Treatment_Months > 180: +3 Failure Points b) If TcQ_mass < 10000: +2 Failure Points c) If Genetic_Class_B_Matches > 3: +1 Failure Point Omicron Complex: - Outcome Determination: a) If TcQ_mass = 0: +4 Failure Points b) If Treatment_Months > 150 AND TcQ_mass < 20000: +3 Failure Points c) If TcQ_mass > 40000: +2 Success Points d) If Genetic_Class_A_Matches > 2: +1 Success Point 2. Advanced Modifiers: - Sex Impact: * Female with low TcQ_mass: +1 Failure Point * Male with high genetic match diversity: -1 Failure Point - Cohort Adjustment: * Melbourne: Neutral * Delhi: Slight success bias (-0.5 Failure Points) * Lisbon: Slight failure bias (+0.5 Failure Points) 3. Final Outcome Calculation: - Total Point Ranges: * Points > 3: Strong FAILURE Prediction * Points < -2: Strong SUCCESS Prediction * Points between -2 and 3: Requires Careful Investigation 4. Confidence Calibration: - High uncertainty zones: * Extreme TcQ_mass values * Borderline genetic match counts * Treatment durations near threshold transitions Evaluation Process: 1. Identify Histogen_Complex 2. Calculate comprehensive point-based risk assessment 3. Apply advanced sex and cohort modifiers 4. Make probabilistic prediction with explicit confidence levels