In a subsequent phase, we incorporated molecular context into the model's architecture with the bestperforming graph convolutional operator, identified as GINE. This was achieved by applying additive pooling to the node representations {h 1 , ..., h |V | } i of the molecular graph G i and concatenating the pooled representation to the representation of the individual nodes j constituting G i . We call this strategy molecular context-pooling.