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The region of heavy calcium isotopes forms the frontier of experimental andtheoretical nuclear structure research where the basic concepts of nuclearphysics are put to stringent test. The recent discovery of the extremelyneutron-rich nuclei around $^{60}$Ca [Tarasov, 2018] and the experimentaldetermination of masses for $^{55-57}$Ca (Michimasa, 2018] provide uniqueinformation about the binding energy surface in this region. To assess theimpact of these experimental discoveries on the nuclear landscape's extent, weuse global mass models and statistical machine learning to make predictions,with quantified levels of certainty, for bound nuclides between Si and Ti.Using a Bayesian model averaging analysis based on Gaussian-process-basedextrapolations we introduce the posterior probability $p_{ex}$ for each nucleusto be bound to neutron emission. We find that extrapolations for drip-linelocations, at which the nuclear binding ends, are consistent across the globalmass models used, in spite of significant variations between their rawpredictions. In particular, considering the current experimental informationand current global mass models, we predict that $^{68}$Ca has an averageposterior probability ${p_{ex}\approx76}$% to be bound to two-neutron emissionwhile the nucleus $^{61}$Ca is likely to decay by emitting a neutron(${p_{ex}\approx 46}$ %).

Neutron drip line in the Ca region from Bayesian model averaging