This analysis highlights the significant impact of data quality on model performance. However, when faced with poor predictive outcomes, such investigations alone may not reveal whether the underlying issue is due to insufficient data coverage or noisy labels. This underscores the need for comprehensive uncertainty measures, which are crucial for diagnosing model failures and gaining deeper insights into model behavior. 1 All models were built using the GINE convolutional operator with context pooling.