Effective Channel Utilization (ECU) is a metric that measures the fraction of time a wireless channel is successfully used for transmission, accounting for interference from neighboring nodes. Prior work introduced an ECU-based jamming detection algorithm that triggers channel reallocation with empirically selected thresholds γ₁ and γ2 and was validated through OPNET simulation. However, the threshold parameters were set without formal characterization of the interference range where the ECU metric is sensitive to changes, leaving the operating boundaries of the detection system undefined. This work addresses that gap by developing an AUC-based transition zone characterization method that identifies and bounds the region of the ECU-interference curve where meaningful detection decisions can be made. A representative ECU-interference dataset was generated using an NS-3 employing a logistic packet success function to sweep 33 interference levels matching the original data. The transition zone analysis was applied to both the original OPNET dataset and the representative dataset at five AUC percentage levels (5%, 10%, 15%, 20%, and 25%). The 10% AUC region was found to provide the most operationally relevant characterization maintaining a steep average decline rate of 0.86 per picoWatt in the original data. The analysis independently corroborated the empirical choice of γ₁ = 0.15 as falling near the center of the transition zone. Additionally, the comparison between the staircase structure of the original data and the smooth decline of the representative data revealed that detection systems with plateau ECU behavior tolerate a wider range of threshold values, while those with continuous declining ECU behavior require tighter calibration.