Introduction Systematic reviews in precision oncology rely on identifying randomized controlled trials (RCTs) to compare therapies and guide clinical decisions. However, screening thousands of articles to find eligible RCTs is labor-intensive and prone to human error. While supervised learning can accelerate this process, it often demands large labeled datasets and careful tuning, especially for nuanced…