Round 473

Round UUID: 86b85f02-03aa-4340-83d9-e704ca4286a7

Prompt:

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

Apply these rules in order:

1. If ParadoxCount < 1.5, predict DENIED (extremely low paradox tolerance is always denied)

2. If TimelineDeviation >= 7.0 AND ParadoxCount >= 6.0, predict APPROVED (moderate timeline deviation with high paradox tolerance)

3. If TimelineDeviation >= 8.0 AND ParadoxCount >= 3.0, predict APPROVED (good timeline deviation with decent paradox tolerance)

4. If TimelineDeviation >= 10.0 AND ParadoxCount >= 2.0, predict APPROVED (high timeline deviation with minimal paradox tolerance)

5. If TimelineDeviation >= 12.0 AND ParadoxCount >= 1.5, predict APPROVED (very high timeline deviation overrides low paradox tolerance)

6. If ParadoxCount >= 8.0, predict APPROVED (extremely high paradox tolerance compensates for low timeline deviation)

7. Otherwise, predict DENIED

Respond with only "APPROVED" or "DENIED".

• Inferences: 200
• Created: 2025-08-01 04:00:30.196050+00:00
• First inference: 2025-08-01 04:00:42.574162+00:00
• Last inference: 2025-08-01 04:18:11.955856+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)