New Sampling Stage for faster quality assurance

The sampling stage feature provides users with an efficient way to conduct quality assurance on large datasets. Instead of manually reviewing every item in the dataset, the sampling stage enables users to select a small subset of data for QA, for example a random 20% sample. This feature is particularly valuable for teams working with specialists such as radiologists, who are paid on an hourly basis. By using the sampling stage, AI teams can reduce the costs associated with manual review by selecting only the amount of data that needs to be reviewed by specialists.