On the one hand, it is possible that different models/methods identify the same set of important features (high similarity) and the performance difference in prediction is due to how different models weigh these important features.
while we focus on consistent patterns across classification tasks, it is certainly interesting to investigate how properties related to tasks and data affect the findings.