The reason we can be so bold with these predictions without even specifying the material in question is that significant aging introduces hidden information that limits the functional relationship between the properties of the initial and aged material. Two adhesive samples may begin the same, but after a year during which one is subjected to outdoor temperature fluctuations and the other is preserved in a warehouse they will likely exhibit dramatic mechanical differences. This is why the irreducible error of a model based solely on initial material definition will be predictably high. Contrarily, some might argue that they can still train a model to predict the aging of a material within some narrow window of aging-histories (e.g., aging in a warehouse). Such a model xvii would only be superficially useful, as the central challenge of modeling aging lies in the potential range of aging-histories.