Round 472

Round UUID: 6b8c5b9f-d230-4317-9149-37f9c0df2888

Prompt:

You are evaluating temporal anomaly cases for approval or denial based on TimelineDeviation and ParadoxCount metrics.

Apply these rules in order:

1. If TimelineDeviation >= 15.0, predict APPROVED (very high timeline deviation overrides other concerns)

2. If ParadoxCount >= 8.0, predict APPROVED (extremely high paradox tolerance)

3. If TimelineDeviation >= 12.0 AND ParadoxCount >= 3.0, predict APPROVED (high timeline deviation with moderate paradox tolerance)

4. If TimelineDeviation >= 10.0 AND ParadoxCount >= 4.0, predict APPROVED (moderate timeline deviation with good paradox tolerance)

5. If TimelineDeviation >= 8.0 AND ParadoxCount >= 6.0, predict APPROVED (lower timeline deviation compensated by high paradox tolerance)

6. If ParadoxCount < 2.5, predict DENIED (insufficient paradox tolerance regardless of other factors)

7. Otherwise, predict DENIED

Respond with only "APPROVED" or "DENIED".

• Inferences: 200
• Created: 2025-08-01 03:57:40.383197+00:00
• First inference: 2025-08-01 03:57:51.032332+00:00
• Last inference: 2025-08-01 04:00:29.716853+00:00
• Completed: yes
• Train accuracy: 0.0 (KT 2.604)
• Validation accuracy: 0.0 (KT 2.604)
• Test accuracy: 0.0 (KT 2.604)