Machine Learning for Alkali-Activated Concrete: Feature Attribution, Strength–Carbon Relationships, and the Limits of Out-of-Campaign Generalisation
Machine learning (ML) models for alkali-activated concrete (AAC) are almost universally evaluated with random train–test splits, yet the literature-compiled datasets are strongly clustered by source study, and the reliability of such evaluations has rarely been quantified. The novelty of this study is a systematic quan...