On Arbitrary Predictions from Equally Valid Models

ArXi:2507.19408v2 Announce Type: replace-cross Model multiplicity refers to the existence of multiple machine learning models that describe the data equally well but may produce different predictions on individual samples. In medicine, these models can admit conflicting predictions for the same patient -- a risk that is poorly understood and insufficiently addressed.