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This is the first official release version of replicAnt! While the full GitHub version (at the time of release) is largely functionally identical, we recommend using the replicAnt_v1.0.0.zip file below for active use to reduce the file size of the project on your computer, in case you do not wish to actively partake in developing replicAnt further and instead need a clean local copy. Refer to the official replicAnt documentation for installation and usage instructions. Notes make sure to additionally download replicAnt external content files and unpack the files into the Content directory of the replicAnt project. (see details in the installation guide) Minimum system requirements: Windows 10 (other operating systems may work but are untested) ~ 50 GB of disk space (the faster the better) Unreal engine itself will occupy roughly 30 GB Another ~5GB are required for the complete project including 3D assets and materials As a rough guide, 10k sample dataset at 2k resolution require ~5 GB (assuming all pass types are required) Dedicated GPU with 6GB VRAM (currently only tested on NVIDIA GPUs) 16 GB RAM
| 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 |
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