Round UUID: 9376bd30-1b57-45d4-8be7-0de3d28213a9
Prompt:
Classification Decision Rules: Metric 1: TimelineDeviation Scoring - If TimelineDeviation > 15: Add 3 points to APPROVAL score - If 12 < TimelineDeviation ≤ 15: Add 2.5 points to APPROVAL score - If 10 < TimelineDeviation ≤ 12: Add 2 points to APPROVAL score - If 8 < TimelineDeviation ≤ 10: Add 1.5 points to APPROVAL score - If 7 < TimelineDeviation ≤ 8: Add 1 point to APPROVAL score - If 5 ≤ TimelineDeviation < 7: Interpolate 1-1.5 points to DENIAL score - If TimelineDeviation < 5: Add 2-3 points to DENIAL score Metric 2: ParadoxCount Scoring - If ParadoxCount > 6: Add 3 points to APPROVAL score - If 4 < ParadoxCount ≤ 6: Add 2.5 points to APPROVAL score - If 3 < ParadoxCount ≤ 4: Add 2 points to APPROVAL score - If 2 < ParadoxCount ≤ 3: Add 1.5 points to APPROVAL score - If 0 < ParadoxCount ≤ 2: Add 1 point to DENIAL score - If ParadoxCount ≤ 0: - Add 2-3 points to DENIAL score - Apply a penalty modifier for extremely low/negative values Special Edge Case Handling: - For ParadoxCount < 0: * If absolute value of ParadoxCount is > 2: - Increase DENIAL score by additional 0.5-1 point - Reduce potential APPROVAL score by a compensatory factor Interaction and Compensation Rules: - If TimelineDeviation > 10 AND ParadoxCount < 3: Add 0.5 bonus points to APPROVAL score - If TimelineDeviation < 7 AND ParadoxCount > 5: Add 0.5 bonus points to DENIAL score - Compensatory Mechanism: - If metrics are divergent (one high, one low): * Apply a sliding penalty/bonus from 0.25 to 1 point * Penalty proportional to degree of metric divergence Final Classification: - If APPROVAL score ≥ 4: Classify as APPROVED - If DENIAL score ≥ 4: Classify as DENIED - Borderline Zone (APPROVAL score 3.5-4, DENIAL score 3.5-4): * Use weighted interpolation based on precise metric values * Slight lean towards APPROVED if TimelineDeviation > 10 * Slight lean towards DENIED if TimelineDeviation < 7 - If scores are exactly tied or within 0.5 points: Require additional review Tiebreaker Criteria: - Prioritize interpolated scoring to reduce binary cliff effects - Consider granular metric interactions comprehensively - Give slightly more weight to TimelineDeviation in close decisions