 Both probabilistic and plausibilistic perspectives can express that some alternative is more likely than another. However, there are also conceptual differences between the two frameworks. Probabilistic models can aggregate, allowing their logic to express, for instance, whether many low-probability events combined can outweigh even the highest-probability worlds. Aggregated probabilities play a key role, for instance, in calculations of expected utility. Yet no such thing can be expressed in plausibility semantics. For another striking difference, plausibility models lead to a notion of belief that is closed under conjunction. This conjunction closure typically fails for probabilistic accounts of belief. See however Leitgeb (2017) for a sophisticated bridge between both types of modeling. 