Evaluation Results
205-sample benchmark across 15+ categories -- real metrics computed from methodD statistical analysis
ROC Curve
Receiver Operating Characteristic -- AUC = 0.781
Confusion Matrix
205 total predictions
Predicted
Actual
AIHuman
AI
61TP
44FN
Human
15FP
85TN
Overall accuracy: 71.2%
Summary Statistics
Key performance metrics
| Metric | Value |
|---|---|
| Accuracy | 71.2% |
| Precision | 80.3% |
| Recall | 58.1% |
| F1 Score | 67.4% |
| AUC-ROC | 0.781 |
| Cohen's Kappa | 0.428 |
| Cohen's d | 1.184 |
| Samples | 205 |
Per-Domain Accuracy
Classification accuracy across content categories
Ablation Study
Full signal vs. individual sub-signal F1 scores
Evaluation performed on a curated 205-sample benchmark spanning 15 content domains. All metrics computed from real methodD statistical analysis with threshold optimized via Youden's J statistic. AUC computed via trapezoidal integration.