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ZENODO
Dataset . 2020
License: CC BY
Data sources: Datacite
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
ZENODO
Dataset . 2020
License: CC BY
Data sources: Datacite
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ZENODO
Dataset . 2020
Data sources: Datacite
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Evaluating the microscopic effect of brushing stone tools as a cleaning procedure [Python analysis]

Authors: Pedergnana, Antonella; Calandra, Ivan; Bob, Konstantin; Gneisinger, Walter; Paixao, Eduardo; Schunk, Lisa; Hildebrandt, Andreas; +1 Authors

Evaluating the microscopic effect of brushing stone tools as a cleaning procedure [Python analysis]

Abstract

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

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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).
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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.
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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).
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