Schematic view of the architecture of the ML models used in this work. The input includes the cropped stamp cube, the FFT cutout, and additional metadata. Both the stamp cube and FFT cutout undergo rotation and flip augmentation before being processed through separate convolutional blocks (red long-dashed boxes). The outputs are then concatenated with the metadata and passed through a fully connected block for prediction. The red short-dashed box highlights the addition of the FFT block to the architecture, which was included in models D, E, and F (see Sect. 2.2).