I explore the traditional contention that a priori epistemic warrants enjoy some sort of higher epistemic security than empirical warrants. By focusing on warrants that might plausibly be called 'basic', and by availing myself of an original taxonomy of epistemic defeaters, I defend a claim in the vicinity of the traditional contention. By discussing some examples, I argue that basic a priori warrants are immune to some sort of empirical defeaters, which I describe in detail. An important by-product of my investigation is a novel theory of epistemic defeaters, according to which only agents able to engage in higher-order epistemic thinking can suffer undermining defeat, while wholly unreflective agents can, in principle, suffer overriding defeat.

<p dir="ltr">Axial spondyloarthritis (axSpA), a disease that due to its complexity and rarity, presents challenges in diagnosis. With a focus on integrating expert knowledge into an intelligent diagnostic system, the research explores the intricate nature of axSpA, emphasizing the challenges associated with its diverse clinical presentation. By leveraging a comprehensive knowledge base curated by domain experts, encompassing insights into pathophysiology, genetic factors, and evolving diagnostic criteria of axSpA, the expert system strives to provide a nuanced understanding of the disease. The methodology employs a hybrid reasoning approach, combining both forward and backward chaining techniques. Forward chaining iteratively processes clinical data and available evidence, applying logical rules to infer potential diagnoses and refine hypotheses, while backward chaining starts with the desired diagnostic goal and works backward through the knowledge base to validate or refute hypotheses. Additionally, certainty theory is incorporated to manage uncertainty in the diagnostic process, assigning confidence levels to conclusions based on the strength of evidence and expert knowledge. By integrating knowledge base, forward and backward chaining, and certainty theory, the research aims to enhance diagnostic precision for this less common yet impactful inflammatory rheumatic condition, emphasizing the importance of early and accurate identification for effective management and improved patient outcomes. The results indicate a significant improvement in diagnostic accuracy, sensitivity, and specificity compared to traditional methods. The system's potential to enhance early diagnosis and treatment outcomes is discussed, along with suggestions for future research to further refine and expand the system.</p>