With global mobile phone penetration nearing 100%, cellular Call Data Records (CDRs) provide a large-scale and ubiquitous, but also sparse and skewed snapshot of human mobility. It may be difficult or inappropriate to reach strong conclusions about user movement based on such data without proper understanding of user movement between call records. Based on an analysis of a real-world trace, we propose a novel, probabilistic Inter-Call Mobility (ICM) model of users' position in between calls. The ICM model combines Gaussian mixtures to build a general, comprehensive spatio-temporal refinement of CDRs.We demonstrate that ICM model's application yields strikingly different conclusions to the existing models when applied to basic CDR analyses, such as user proximity probability.