As a junior Data Scientist at a rapidly growing e-commerce company, you're tasked with developing a logistic regression model to categorize customer support text messages into 'urgent/important' and 'non-urgent/unimportant'. The model's performance is critical for prioritizing customer issues efficiently. You need to select an evaluation metric that not only assesses the model's ability to distinguish between these two classes but also adheres to the following requirements: it must be scale invariant and classification threshold invariant. Additionally, the company emphasizes the importance of minimizing false positives to avoid misallocating resources. Given these constraints, which of the following methodologies should you choose? (Choose two correct options if E is available, otherwise choose one.)