Which options are needed for the Reviewed Field on an Active Learning coding panel?

The requirement for the Reviewed Field on an Active Learning coding panel includes designating items that are identified as Positive or Responsive. This designation is crucial because it helps in guiding the machine learning algorithms to focus on documents that are relevant to the issues being investigated. By classifying documents as Positive or Responsive, reviewers provide clear signals that enhance the accuracy of the predictive coding model. This improves the efficiency of the review process by allowing the system to prioritize the most pertinent documents based on these designations.

In the context of Active Learning, having these clear indicators helps the model learn effectively from the labeled data, thus refining its predictive capabilities over time. This contrasts with other options that might include designations such as Negative or Neutral, which, while important in the overall review process, do not specifically fulfill the requirement for the Reviewed Field within this context. Therefore, the focus on Positive/Responsive designation is critical in training the machine learning model for effective document classification.