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Table 2 Results of re-ranking combined proposals of GLN and RetroSim on USPTO-50K test data

From: Improving the performance of models for one-step retrosynthesis through re-ranking

Models Top-N accuracy (%) Mean Reciprocal Rank
1 3 5 10 20 50
RetroSim 35.7 (\(\pm 0\)) 53.3 (\(\pm 0\)) 62.0 (\(\pm 0\)) 73.4 (\(\pm 0\)) 82.3 (\(\pm 0\)) 88.5 (\(\pm 0\)) 0.477 (\(\pm 0.000\))
RetroSim + Graph-EBM 51.8 (\(\pm 0.43\)) 74.5 (\(\pm 0.37\)) 81.1 (\(\pm 0.17\)) 86.4 (\(\pm 0.13\)) 88.5 (\(\pm 0.02\)) 88.9 (\(\pm 0.00\)) 0.644 (\(\pm 0.004\))
GLN 51.7 (\(\pm 0.33\)) 67.8 (\(\pm 0.43\)) 75.1 (\(\pm 0.32\)) 83.2 (\(\pm 0.12\)) 88.9 (\(\pm 0.11\)) 92.4 (\(\pm 0.06\)) 0.620 (\(\pm 0.003\))
GLN + Graph-EBM 52.3 (\(\pm 0.01\)) 74.9 (\(\pm 0.27\)) 82.0 (\(\pm 0.18\)) 88.0 (\(\pm 0.02\)) 91.4 (\(\pm 0.11\)) 93.0 (\(\pm 0.08\)) 0.652 (\(\pm 0.001\))
GLN + RetroSim + Graph-EBM 52.5 (\(\pm 0.10\)) 75.7 (\(\pm 0.15\)) 83.1 (\(\pm 0.34\)) 89.7 (\(\pm 0.18\)) 93.1 (\(\pm 0.12\)) 94.8 (\(\pm 0.06\)) 0.658 (\(\pm 0.000\))
  1. Bolded values represent best top-N accuracies and best MRR across both GLN and RetroSim (including their individually re-ranked versions)