1. Introduction  
2. The Dark Energy Survey and Transient Detection Pipeline  
3. Classifier Development  
3.1. Training Data  
3.2. Features and Processing  
3.3. Classification Algorithm Selection  
3.4. Feature Importances  
3.5. Optimization  
4. Performance  
4.1. Performance Metrics  
4.2. Classification Task  
4.3. Results  
4.4. Effect of autoScan on Transient Candidate Scanning Load  
5. Discussion  
5.1. Automating Artifact Rejection in Future Surveys  
5.2. Eliminating Spurious Candidates