While the above analysis provides insights into the performance of the model in different scenarios, obtaining deeper physical insights into why these discrepancies occur is a more complex task. Due to the nature of deep learning models with billions of parameters, they tend to be less explainable, making it difficult to extract detailed physical explanations.