For performance evaluation, two different measures were used: Predictions identical to the correct molecule were considered to be the optimal result, of course. But predictions resembling the correct molecule closely are also very useful for the curation of chemical data. A human curator, for example, who is presented with the bitmap image and an already very similar machine translation only needs to perform a small correction with a chemical structure editor as opposed to re-drawing the whole molecule. To evaluate the similarity of molecular structures, the Tanimoto similarity or Jacard-Index is used, which encodes the presence or absence of structural features of chemical compounds in a bit vector (where PubChem fingerprints were used in particular) and expresses the similarity between two bit vectors (or two chemical structures, respectively) as a number between 0.0 (most dissimilar) and 1.0 (most similar).