Your question is Explain Model Calibration Importance. Take a moment with it on the right.
Talk me through your thinking if you like. When you're confident, submit your answer and I'll grade it like a real screen (7/10 or better passes).
You have a classification model that outputs probabilities, and stakeholders want to use those scores for decisions, not just ranking. You need to explain how to judge whether a score like 0.8 really means an 80 percent chance of the event.
What does calibration mean in model evaluation, and why is it important?