Not totally sure I understand your question but I’ll give it a shot.
The metrics are just things like accuracy or beta scores - basically they are a quick way to see how your model is performing catered to a certain judgement.
You are correct in the way that the threshold works. If the model finds an object with 55% certainty, it will classify the image as having the object since default threshold is 50%. So, changing this threshold really only changes the likelihood of classes being identified. For example, in one of my projects, my model usually has about a 99% chance of a class if it exists. Often, it will show a 80% chance of a class that doesn’t exist. To fix this, I changed the threshold to 90% in order to discard these false positives while maintaining accuracy for the correctly labeled classes.