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doi: 10.5281/zenodo.28659 , 10.5281/zenodo.34089 , 10.5281/zenodo.29945 , 10.5281/zenodo.35293 , 10.5281/zenodo.33755 , 10.5281/zenodo.33754 , 10.5281/zenodo.33459 , 10.5281/zenodo.35284 , 10.5281/zenodo.29907 , 10.5281/zenodo.34099 , 10.5281/zenodo.17581 , 10.5281/zenodo.34087 , 10.5281/zenodo.592722
doi: 10.5281/zenodo.28659 , 10.5281/zenodo.34089 , 10.5281/zenodo.29945 , 10.5281/zenodo.35293 , 10.5281/zenodo.33755 , 10.5281/zenodo.33754 , 10.5281/zenodo.33459 , 10.5281/zenodo.35284 , 10.5281/zenodo.29907 , 10.5281/zenodo.34099 , 10.5281/zenodo.17581 , 10.5281/zenodo.34087 , 10.5281/zenodo.592722
pyfssa is a scientific Python package for algorithmic finite-size scaling analysis at phase transitions
Initial release
| 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). | 11 | |
| 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. | Top 10% | |
| 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 |
| views | 64 | |
| downloads | 6 |

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