A Sift Score is a number between 0 and 100 where 0 indicates that the user is safe and 100 indicates that the user is risky.
To find your ideal block/review/accept score thresholds, look for a score where you're seeing that most of the users above it are fraud. Since each business has different considerations for the right percentage of users to block, false positives to allow (good users blocked), and fraud to catch based on automation, you'll need to do some evaluation - we're happy to help so feel free to reach out.
A high score in one abuse type does not tell you that a user will go on to commit fraud in another. So, a user could have a low score for Content Abuse and a high score for Payment Abuse, suggesting you're at risk of payment fraud from this user but not content fraud. However, you'll often only see one score at a time as you would check for Content Abuse score when users post content and the Payment Abuse score when users make a purchase. Also, your score thresholds will likely vary between the different fraud and abuse types you're using Sift to prevent.