
mols/ contains PubChem IDs for all source molecules. ind* denotes training sets, val* validation sets, and test.txt the test set. pairs/ contains molecular pairs (excluding self-pairs) and Tanimoto similarities in the form of HDF5 files. priors/ contains final model checkpoints. data_pipeline.toml is the configuration file used for pre-processing using the REINVENT4 data pipeline (version 4.5). custom_loader.py is a custom dataloader that was used along with the training code from this GitHub repository. Data in the HDF5 files can be accessed like so: import h5py f = h5py.File("pairs/val161K/final_0.h5py") # Keys are PubChem IDs keys = f.keys() # Loop over all pairs for key in keys: data = f[key] for pair in data: # (source ID, target ID, similarity) print(pair)
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
