By blocking out specific regions of input data, the model's predictions shifted dramatically when essential features were obscured, confirming its focus on relevant indicators of planetary transits. This meticulous examination led to valuable visualizations and explanations that not only validated the model's learning process but also enhanced understanding of its decision-making.
