Metabolic reactions are critical in determining the efficacy and safety of agrochemicals, pharmaceuticals, industrial chemicals, and other xenobiotic compounds . These biotransformations, catalyzed by xenobiotics-metabolizing enzymes, include a range of reactions such as functionalizations, hydrolysis, and conjugations, which generally increase the polarity of compounds to facilitate their excretion . While these enzymatic processes typically contribute to detoxification, they can also generate reactive intermediates or metabolites that disrupt essential physiological functions -a phenomenon known as toxification . For instance, hydroxylated metabolites of polychlorinated reduced with additional information . Epistemic uncertainty is further divided into model bias, or model uncertainty, and variance, also known as approximation uncertainty. Model bias arises from choices related to data representation and model architecture. It is usually ignored when working within a specific predictive setting. In contrast, variance relates to ambiguities in the model's learned parameters after its architecture has been selected and is expected to disappear in the limit of infinite data .