so we get back the original definition of Kolmogorov complexity in that special case. With this generalised definition of Kolmogorov randomness in hand, it turns out that we can show a generalisation of Schnorr’s theorem (§2.3): a sequence \(\sigma\) is \(\lambda\)-incompressible iff \(\sigma\) is ML-random with respect to \(\lambda\).[15] In the framework of supplement B.1.1, a sequence is ML-random in this generalised sense iff the measure, under our arbitrary computable measure \(\lambda\), of the \(n\)th sequential significance test is no greater than \(1/2^n\). (There are some potential pitfalls, suggesting that perhaps the generalisation to an arbitrary computable measure is an overgeneralisation: see supplement B.1.3 for some details.)