It's logits or log odds or the logarithm of the odds, i.e. log(odds(p)) = log(p / (1 - p)): https://en.wikipedia.org/wiki/Logit https://en.wikipedia.org/wiki/Lo

It's logits or log odds or the logarithm of the odds, i.e. log(odds(p)) = log(p / (1 - p)): https://en.wikipedia.org/wiki/Logit https://en.wikipedia.org/wiki/Logit Since sigmoid(C(x_r)) = p(x_r is real) and C(x_f) = p(x_f is real), the sigmoid of the difference expresses some probability that that x_r looks more real than x_f or vice versa (depending on whether it is C(x_r) - C(x_f) or C(x_f) - C(x_r)). Not sure whether there is a probabilistic interpretation of the difference, but it looks so simple that there maybe is one. I couldn't find one in the paper.