 Consequently, Andreas (2018) generalized the present semantics so as to capture scientific reasoning in a paraconsistent setting. The proposal is based on a preferred-models semantics: satisfaction of a theory and agreement with empirical data comes in degrees. Some interpretations score better than others. This idea leads to a strict partial order of interpretations. And we understand the theoretical terms in such a manner that the set of instances of all the axioms is satisfied to a maximal extent in the context of a given interpretation of the observation terms. This proposal parallels certain adaptive logics, developed by Batens (2000) and Meheus et al. (2016). Notably, it allows us to capture scientific reasoning with ceteris paribus laws, i.e., laws that hold true most of the time but have exceptions. This could be helpful for the analysis of theoretical terms in scientific disciplines other than physics.