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This software contains the code and presentation from the conference paper `` Comparing FSPMs using Unconventional Computing Methods'', presented at FSPM2023 in Berlin. The software to run the analysis can be found on [Github](https://github.com/opieters/fspm2023). The YAML-files (`hydroshoot_environment.yml`, `wheatfspm_environment.yml`) should be used to create the anaonda environments and reproduce the output CSV files. The files are also included for convenience (`hydroshoot.zip` and `WheatFspm.zip`). The source code is also included here in case the original repositories are no longer available on GitHub. The code for the grass leaf model is not yet available because the research paper has not yet been published. The input files (`*_meteo.csv`) is the input meteorological data. The output files all end with `_data.csv`. Import these into the `data` directory from the GitHub code and you should be able to reproduce the results.
| 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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