What calibration buys you

A model that says 0.9 should be right nine times out of ten. If it’s right only six times, the number is decoration. If it’s calibrated, the number becomes a control you can build on.

Why it matters

Calibration lets you set a simple rule: act automatically above a threshold, send everything else to a person or a larger model. You can predict, before you ship, how much work gets automated and how many mistakes slip through.

How we measure it

We track three things. Accuracy tells you how often the top answer is right. Brier score tells you how far the probabilities are from what actually happened. Expected calibration error compares stated confidence with real accuracy across ten confidence bins, before and after we fit the temperature.

We also check whether answers change when options are reordered. A calibrated model that flips its answer when you swap two options isn’t one you should trust.

Measure on your own data. Calibration on our test set is a starting point, not a guarantee for your traffic.