AI Learns Geochemistry: New Explainable Model Targets Rare Earth Deposits
Researchers have developed EBGT, an explainable machine learning framework that embeds geochemical constraints into gradient-boosted trees to identify ion-adsorption rare ...
Researchers have developed EBGT, an explainable machine learning framework that embeds geochemical constraints into gradient-boosted trees to identify ion-adsorption rare ...
Researchers at Bahir Dar University have built an ensemble lip-reading model for Amharic that combines Gabor filters, Capsule Networks, and ...
A machine-learning web application trained on hundreds of finite element simulations delivers near-instant rock-slope stability forecasts for seismically active mountain ...
A Kazakhstani research team shows that physically structured features and calibrated baselines, not model architecture, drive a tenfold improvement in ...
Researchers trained machine learning models on satellite oceanographic data to accurately predict microplastic abundance across the Indian Ocean.
An optimized gradient boosting model predicts biochar cation exchange capacity with high accuracy from biomass composition and pyrolysis conditions, validated ...
A new triboinformatics study uses gradient boosting, deep learning, and interpretable AI to accurately predict wear and friction in Nitinol ...
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© 2026 Scienmag - Science Magazine