Now that the various approaches for predicting TS geometries have been discussed in detail, it is important to address the challenges in directly comparing these methods. A key limitation arises from the fact that the models were developed at different times, using distinct datasets, with varied splits between training and tests sets, and run on different hardware. These factors can impact model performance, making direct comparisons of performance metrics challenging.