There continues to be a vigorous public debate in our society about the status of climate
science. Much of the skepticism voiced in this debate suffers from a lack of understanding of …

In climate science, observational gridded climate datasets that are based on in situ
measurements serve as evidence for scientific claims and they are used to both calibrate …

The explainable AI literature contains multiple notions of what an explanation is and what
desiderata explanations should satisfy. One implicit source of disagreement is how far the …

The term robustness is ubiquitous in modern Machine Learning (ML). However, its meaning
varies depending on context and community. Researchers either focus on narrow technical …

This essay develops a joint theory of rational (all-or-nothing) belief and degrees of belief.
The theory is based on three assumptions: the logical closure of rational belief; the axioms of …

In everyday life we normally express our beliefs in all-or-nothing terms: I believe it is going to
rain; I don't believe that my lottery ticket will win. In other cases, if possible, we resort to …

Human microbiome research makes causal connections between entire microbial
communities and a wide array of traits that range from physiological diseases to …

Agent-based simulations have become increasingly prominent in various disciplines. This
trend is positive, but it comes with challenges: while there are more and more standards for …

We claim that the process of theoretical model refinement in economics is best characterised
as robustness analysis: the systematic examination of the robustness of modelling results …

This article identifies conditions under which robust predictive modeling results have special
epistemic significance—related to truth, confidence, and security—and considers whether …