Class OutlierDetector

Detects anomalous feedback records that should be quarantined and excluded from learning.

Criteria:

• duration above 10x the median
• failure with decision confidence above 0.95
• code complexity increase above 50%
• duration below 10 ms (likely corrupted timing data)