In recent years, there has been increasing interest in the logical constraints of scientific reasoning that make possible the rational use of defective—e.g. false, imprecise, conflicting, incomplete, inconsistent, partial, ambiguous, and vague—information in scientific contexts. On the one hand, for a variety of causes, scientific information is often inaccurate, poorly empirically supported, and not as relevant as it should be. As a matter of fact, the defective character of scientific data is not only ubiquitous but inevitable. Despite this, scientists have proven to be able to work with such defects and reach significant degrees of scientific success, such as accurate predictions, descriptions, and explanations (see Smith 1988; Brown 1990; Batens 2002, 2017; Meheus 2002; Brown and Priest 2004, 2015; Bueno 2006, 2017; Friend 2017; Heyninck, Verdée and Heeffer 2017; Šešelja 2017; Friend and Martinez-Ordaz 2018; Martinez-Ordaz 2020). On the other hand, traditional formal approaches to scientific and—more broadly—human reasoning have not fully and properly explained why and how such success is achievable in defective contexts. However, recent works in philosophical logic have shown that any successful analysis of scientific reasoning must pay attention to: