Mixture replication in benchmark datasets inflates reported machine learning performance and degrades prediction interval coverage for ultra-high-performance concrete
Machine learning models for ultra-high-performance concrete (UHPC) commonly report coefficients of determination above 0.94 on held-out records, and these values now shape expectations for data-driven mix design. We show that a substantial part of this reported predictive performance depends on how the models are eva...