Argumentation is a well-established formalism for nonmonotonic reasoning and a vibrant area of research in AI. Claim-augmented argumentation frameworks (CAFs) have been introduced to deploy a conclusion-oriented perspective. CAFs expand argumentation frameworks by an additional step which involves retaining claims for an accepted set of arguments. We introduce a novel concept of a justifcation status for claims, a quantitative measure of extensions supporting a particular claim. The wellstudied problems of credulous and skeptical reasoning can then be seen as simply the two endpoints of the spectrum when considered as a justifcation level of a claim. Furthermore, we explore the parameterized complexity of various reasoning problems for CAFs, including the quantitative reasoning for claim assertions. We begin by presenting a suitable graph representation that includes arguments and their associated claims. Our analysis includes the parameter treewidth, and we present decompositionguided reductions between reasoning problems in CAF and the validity problem for QBF.