A chemical company needs a model that maximizes the chance of detecting abnormal process behavior (labels: 0 = normal, 1 = abnormal). Which of these metric pairs indicates the model most likely to detect abnormalities?

The company needs to maximize the chance of detecting abnormal behavior, which means minimizing false negatives. Recall (also known as sensitivity) measures the proportion of actual positive cases that are correctly identified. A high recall value indicates that the model is good at finding all the positive samples. In this scenario, "abnormal behavior" is the positive class. Therefore, the option with the highest recall (0.98) is the most suitable. While precision is lower (0.61), meaning more false positives, the primary goal is detection, making high recall paramount. The other options have lower recall values, meaning they would miss more actual abnormalities.