Tittle: Involvement of Slab‐Derived Fluid in the Generation of Cenozoic Basalts in Northeast China Inferred from Machine Learning
Abstract: The origin and involvement of fluid in the generation of Cenozoic basalts in Northeast China are still under debate. Here we apply the machine learning methods of random forest and deep neural network to train models using data sets of global island arc and ocean island basalts. The trained models predict that most Cenozoic basalts in Northeast China are influenced by fluid and that the fluid activity decreases from east to west. The boundary defined by fluid activity coincides with the westernmost edge of the present‐day stagnant Pacific slab determined by seismic tomography and with the geochemical boundary defined by magnesium isotopes. These observations support the view that the fluid involved in the generation of the basalts is controlled by the stagnant Pacific slab instead of driven by the plume induced by the sinking Izanagi Plate.
Citation: Zhao Y., Zhang Y., Geng M., Jiang J., Zhou X., (2019). Involvement of Slab‐Derived Fluid in the Generation of Cenozoic Basalts in Northeast China Inferred from Machine Learning. Geophysical Research Letter, 46.
