are the reaction centre logits without and with (only) the subgraph provided to the GNN, respectively. Therefore, fid-gauges the importance of the identified subgraph to the model, whereas fid+ gauges whether the GNNExplainer failed to identify important nodes that are not part of GS. Since the GNN model treats the reaction centre identification as a classification (eq. 17 -the reaction centre is the node with the largest z), the fidelity calculation is simplified as fid+ = 1 -1 k * ,G C\S = k * , and fid-= 1 -1 k * ,G S = k * , where k * is defined in Equation . Therefore, the fidelity metrics can only take values of 0 and 1. Finally, the fidelity curve f is calculated through Eq. 20 with a value of 1 indicating a confident subgraph GS containing all important nodes in the graph. A value of 0 would reveal that either important nodes are missing from GS or that GS itself is considered unimportant to the prediction.