A data scientist at a logistics company is building a machine learning model to estimate package delivery times. Before training, she divides her historical dataset into three separate portions. She uses one portion to fit the model, a second portion to tune hyperparameters and compare model configurations during development, and a third portion that she holds back and uses only once, at the very end, to report an unbiased estimate of how the model will perform on new data. What is the third, held-back portion of data commonly called?