In methodology, a significant limitation exists in using traditional techniques for weight assignment. This approach risks introducing bias, as it does not consider the probabilistic nature of olfactory classifications. The consequence is a potential failure to capture the full spectrum of odor intensity variations across different molecular components. This rigidity in weight allocation can limit the model's adaptability to new or complex olfactory scenarios, thereby affecting the overall accuracy and reliability of the odor classification model. A further limitation of methodology is the absence of a mechanism for handling uncertainty. These uncertainties can manifest from the mechanistic models describing perfume diffusion and the variable classifications within olfactory families for individual odorants. Additionally, it is essential to identify, quantify (when feasible), and integrate these uncertainties into the predictive modeling tools used for designing fragrance mixtures.