Music streaming services face a significant threat from fraudsters who artificially inflate stream counts to manipulate chart rankings and royalty payments. To combat this, researchers have developed SAGE, a scalable automatic gating ensemble for confident negative harvesting in fraud detection. SAGE aims to improve upon traditional fraud detection approaches, which often struggle to distinguish between legitimate edge cases and fraudulent activity. By leveraging an ensemble approach, SAGE can more accurately identify and flag suspicious activity, reducing the risk of false positives and negatives. The system's ability to confidently harvest negative examples enables it to improve its detection capabilities over time, making it a valuable tool for music streaming services1. This matters to practitioners because effective fraud detection is crucial for maintaining the integrity of music streaming platforms and ensuring that legitimate content creators are fairly compensated for their work.