Multi-Output Data-Driven Modeling of Age-Dependent Compressive Strength in Slag–CaCO3 Blended Cementitious Systems

The incorporation of slag and calcium carbonate (CaCO3) as clinker-reducing constituents offers significant potential for lowering CO2 emissions in cement production; however, their combined influence on age-dependent compressive strength remains complex and highly coupled. In this study, a structured literature-based dataset (N=75 mix conditions) was compiled from two independent experimental sources to investigate compressive strength development in slag–CaCO3 blended cementitious systems. Compressive strength at 3 and 28 days was formulated as a multi-output regression problem to explicitly capture the correlated nature of strength evolution between early-age and later-age curing stages. Dataset-level analysis revealed that CaCO3 replacement exerts a stronger influence on early-age strength (reductions of approximately 15–25%) than on later-age strength (typically within 5–15%), indicating a transition from clinker-dominated hydration to slag-controlled later-age strength development. Compared with independent single-output models, the proposed multi-output framework improved prediction performance by increasing R2 values by approximately 4–6% and reducing RMSE by up to 15–18%. Feature importance analysis identified slag replacement ratio and CaCO3 dosage as the dominant predictors, while chemical composition descriptors modulated age-dependent sensitivity. The results demonstrate that compressive strength at different curing ages is governed by coupled yet temporally evolving physicochemical mechanisms. From an engineering perspective, CaCO3 replacement should be evaluated within an integrated compositional design framework that considers curing-age requirements and slag reactivity. Overall, this study provides a transparent and statistically robust approach for analyzing strength evolution in blended cement systems and highlights the value of multi-output learning for age-dependent performance prediction in sustainable cementitious materials.