These explainability features provide practical benefits for structure elucidation tasks. By visualizing the model's confidence in structural components, chemists can focus on uncertain aspects, guiding targeted experimental work like selective 2D NMR or chemical derivatization. For multiple suggested structures, confidence visualization aids in prioritizing hypotheses, streamlining the elucidation process. The correlation between prediction probabilities and spectral reconstruction errors offers a metric for assessing prediction reliability, helping chemists decide when to trust the model's suggestions or seek additional experimental evidence. To facilitate practical application of these insights, we have implemented the full improvement cycle workflow as a GUI in the form of an HTML website. This interface includes probability plotting for suggested molecules and allows users to compare simulated spectra of generated molecules with data. The code and user manual are provided in the Supplementary Information Section 7 with explanatory screenshots in Supplementary Figure -Supplementary Figure , offering a powerful tool to elucidate structures based on our MMT model.