Their model is trained only on runs it has seen before which didn't include sufficient full moon runs. So its performance degraded when it encountered a suffici

Their model is trained only on runs it has seen before which didn't include sufficient full moon runs. So its performance degraded when it encountered a sufficiently novel variant. Which is where the I part of AI always falls down, input that sufficiently differs. E.g., train facial recognition on a corpus of predominately white American faces, African Americans suffer a horribly high false positive rate when the cops use your model on surveillance footage.