Strength-Constrained Screening of Lower-CO2 Geopolymer Concrete Mix Designs: Response Matching and Stability Assessment

Public geopolymer concrete (GPC) databases can support retrospective screening of records with lower reported CO2 emissions under strength constraints, but reliable ranking also requires correct response matching and stable threshold-based eligibility. Using 274 records, this study reconstructed the strength–CO2 correspondence from 19 mix proportion and preparation fields, yielding 273 mix design identifiers (MixIDs). Eight regression algorithms were evaluated under MixID-grouped validation, and CatBoost with derived descriptors was retained as the primary model. It achieved R2 = 0.969 and RMSE = 2.096 MPa on the fixed test set; across 30 repeated holdouts, mean RMSE was 2.390 ± 0.234 MPa. Because observed strength was available for every record, the model served as an internal consistency filter rather than a predictor of untested formulations. At 40, 50, and 60 MPa, 176, 65, and four records met the observed strength and mean prediction criteria, while 174, 62, and three records also satisfied the empirical fifth-percentile (Q05) criterion. Q05 was treated as a descriptive measure of partition sensitivity, and the 60 MPa result was regarded as exploratory. A CO2 assignment negative control showed weak agreement between row-wise and key-matched values (Pearson r = 0.065) and low Pareto-set overlap (Jaccard = 0.045–0.105). Thus, prediction accuracy alone does not ensure valid lower-CO2 ranking. The workflow provides an auditable basis for screening observed records within the database domain.