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Related Questions
- What are the key metrics used to assess the accuracy of human annotations in data curation?
- How can data curation teams ensure consistency in their annotation guidelines and practices?
- What role do metrics such as inter-annotator agreement and Cohen's kappa play in evaluating annotation quality?
- What are some common metrics used to measure the reliability of annotations, such as accuracy, precision, and recall?
- How can data curation teams use metrics to identify and address biases in their annotations?
- What is the difference between metrics such as F1-score and precision-recall curve in evaluating annotation quality?
- How can data curation teams use metrics to evaluate the impact of their annotations on downstream machine learning models?
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