A recent Nature study by Kim, Young-sang et al. applied machine learning, notably SVR, to predict the thermal conductivity of steelmaking slag-based fillers. By analyzing normalized AD and HP datasets, the research shows enhanced prediction accuracy over traditional empirical formulas, indicating significant potential in improving geothermal system efficiency.