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This upload includes the following files related to the Python analysis: Raw data as a XLSX table (brushing_v2.xlsx), i.e. results from R Script #1 (see https://doi.org/10.5281/zenodo.3632517) Python script of the whole analysis (RunEveryParameter.py) Convenience script for running RunEveryParameter.py in background and logging all output (RunSingleParametesBash.sh) Log file for output of sampling from the model for each parameter in a loop (logAll.txt) Jupyter notebooks of the analysis run on epLsar as an example (Notebook_SingleParameter.inpyb) and of a summary of the whole analysis (Notebook_Overview.ipynb), plus associated HTML output files (*.html) For each parameter: Full samples of parameter values (*.pkl) Energy plots of Hamiltonian Monte Carlo (*_Energy.pdf) Contrast plots between each treatment (BrushDirt = Is_Is, BrushNoDirt = Is_No, RubDirt = No_Is) and the control (No_No) (*_Contrasts.pdf) Trace plots for each parameter (*_Trace.pdf) Distribution of posteriors for each parameter (*_Posterior.pdf) Prior and posterior predictive distributions for each parameter (*_PriorPosterior.pdf) Instructions to download all files at once are given here: https://doi.org/10.5281/zenodo.4011952
| 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 | |
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| 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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