To improve the recall for the GAK dataset, we next attempted to adjust the failed score parameter: Motivated by our hypothesis, we set the failed score to 0.0 (closer to other obtained docking scores) to reduce the emphasis on failed compounds during training, which improved the recall of the top-scoring 100, 1000, and 10 000 compounds by 9-13% when compared to the failed score of +5.0 (compare Figure and Table ). We tested the same approach for SurA, which did, however, not consistently improve the recall (Table ).