RDTool was the only tool that could not complete all reactions in the Golden and NatComm datasets, see Figure and. These results suggest that Ensemble_2, which includes RDTool, may not be efficient for processing large-scale databases. Additionally, the Biochemical Reaction Dataset posed more challenges compared to the Chemical Reaction Dataset, with processing times more than doubling. log(min) methods achieved the highest accuracies. In the Chemical Reaction Dataset, the difference in performance between Ensemble_1 and Ensemble_2 is marginal, at 99.47% and 99.69%, respectively. However, employing Ensemble_2 decreased the success rate from 71.23% to 67.14% and increased computational expenses due to the integration of RDTool. Despite the effective performance of ensemble strategies on the Biochemical Reaction Dataset, with accuracies of 76.10% for Ensemble_1 and 80.16% for Ensemble_2, the overall success rate remained below 45%. Thus, these results suggested that ensemble strategy, Ensemble_1 in particular, is primarily effective only for the Chemical Reaction Dataset.