stars-reproduce-allen-2020
Test-run of our reproducibility protocol on Allen et al. 2020: "A simulation modelling toolkit for organising outpatient dialysis services during the COVID-19 pandemic"
https://github.com/pythonhealthdatascience/stars-reproduce-allen-2020
Science Score: 67.0%
This score indicates how likely this project is to be science-related based on various indicators:
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✓CITATION.cff file
Found CITATION.cff file -
✓codemeta.json file
Found codemeta.json file -
✓.zenodo.json file
Found .zenodo.json file -
✓DOI references
Found 1 DOI reference(s) in README -
○Academic publication links
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✓Committers with academic emails
1 of 2 committers (50.0%) from academic institutions -
○Institutional organization owner
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○JOSS paper metadata
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○Scientific vocabulary similarity
Low similarity (11.7%) to scientific vocabulary
Keywords
Keywords from Contributors
Repository
Test-run of our reproducibility protocol on Allen et al. 2020: "A simulation modelling toolkit for organising outpatient dialysis services during the COVID-19 pandemic"
Basic Info
- Host: GitHub
- Owner: pythonhealthdatascience
- License: mit
- Language: Jupyter Notebook
- Default Branch: main
- Homepage: https://pythonhealthdatascience.github.io/stars-reproduce-allen-2020/
- Size: 58.6 MB
Statistics
- Stars: 2
- Watchers: 1
- Forks: 0
- Open Issues: 0
- Releases: 3
Topics
Metadata Files
README.md
STARS: Computational reproducibility of Allen et al. 2020 
⚠️ This is a test-run for STARS work package 1 using a paper that Tom Monks was involved with. It was created to help us test out the reproduction protocol and guide creation of the template repository. ⚠️
This repository forms part of work package 1 on the project STARS: Sharing Tools and Artefacts for Reproducible Simulations. It assesses the computational reproducibility of:
Allen, M., Bhanji, A., Willemsen, J., Dudfield, S., Logan, S., & Monks, T. A simulation modelling toolkit for organising outpatient dialysis services during the COVID-19 pandemic. PLoS One 15, 8 (2020). https://doi.org/10.1371%2Fjournal.pone.0237628
Website
⭐ Click here to check out the website for this repository ⭐
This website is created using Quarto and hosted using GitHub Pages. It shares everything from this computational reproducibility assessment, displaying: * The original study article and associated artefacts. * Code and documentation from reproduction of the model. * Evaluation of model reproduction success. * Evaluation of the original study against guidelines for sharing research, criteria for journal reproducibility guidelines, and article reporting guidelines. * Logbook with chronological entries detailing reproduction work. * Final report describing the computational reproducibility assessment.
Protocol
The protocol for this work is summarised in the diagram below and archived on Zenodo: Link to Zenodo once published.

Repository overview
bash
├── .github
│ └── workflows
│ └── ...
├── evaluation
│ └── ...
├── logbook
│ └── ...
├── original_study
│ └── ...
├── quarto_site
│ └── ...
├── reproduction
│ └── ...
├── .gitignore
├── CHANGELOG.md
├── CITATION.cff
├── CONTRIBUTING.md
├── LICENSE
├── README.md
├── _quarto.yml
├── citation_apalike.apa
├── citation_bibtex.bib
├── index.qmd
└── requirements.txt
Key sections: This files have all the content related to the original study and reproduction...
original_study/- Original study materials (i.e. journal article, supplementary material, code and any other research artefacts).reproduction/- Reproduction of the simulation model. Once complete, this functions as a research compendium for the model, containing all the code, parameters, outputs and documentation.evaluation/- Quarto documents from the evaluation of computational reproducibility. This includes the scope, assessment of reproduction success, and comparison of the original study materials against various guidelines, and summary report.logbook/- Daily record of work on this repository.
Other sections: The following files support creation of the Quarto site to share the reproduction, or are other files important to the repository (e.g. README, LICENSE, .gitignore)...
.github/workflows/- GitHub actions.quarto_site/- A Quarto website is used to share information from this repository (including the original study, reproduced model, and reproducibility evaluation). This folder contains any additional files required for creation of the site that do not otherwise belong in the other folders..gitignore- Untracked files.CHANGELOG.md- Description of changes between GitHub releases and the associated versions on Zenodo.CITATION.cff- Instructions for citing this repository, created using CFF INIT.CONTRIBUTING.md- Contribution instructions for repository.LICENSE- Details of the license for this work.README.md- Description for this repository. You'll find a seperate README for the model within thereproduction/folder, and potentially also theoriginal_study/folder if a README was created by the original study authors._quarto.yml- Set-up instructions for the Quarto website.citation_apalike.bib- APA citation generated from CITATION.cff.citation_bibtex.bib- Bibtex citation generated from CITATION.cff.index.qmd- Home page for the Quarto website.requirements.txt- Environment for creation of Quarto site (used by.github/workflows/quarto_publish.yaml).
Citation
If you wish to cite this repository, please refer to the citation file CITATION.cff, and the auto-generated alternatives citation_apalike.apa and citation_bibtex.bib.
License
This repository is licensed under the MIT License.
This is aligned with the original study, who also licensed their work under the MIT License.
Funding
This work is supported by the Medical Research Council [grant number MR/Z503915/1].
Owner
- Name: pythonhealthdatascience
- Login: pythonhealthdatascience
- Kind: organization
- Repositories: 1
- Profile: https://github.com/pythonhealthdatascience
Citation (CITATION.cff)
# This CITATION.cff file was generated with cffinit.
# Visit https://bit.ly/cffinit to generate yours today!
cff-version: 1.2.0
title: Reproducing Allen et al. 2020
message: >-
If you use this software, please cite it using the
metadata from this file.
type: software
# List the authors involved in reproduction: first, the primary researcher,
# followed by those providing advice/feedback on the reproduction.
authors:
- given-names: Amy
family-names: Heather
email: a.heather2@exeter.ac.uk
affiliation: University of Exeter
orcid: 'https://orcid.org/0000-0002-6596-3479'
- given-names: Tom
family-names: Monks
email: t.m.w.monks@exeter.ac.uk
affiliation: University of Exeter
orcid: 'https://orcid.org/0000-0003-2631-4481'
repository-code: >-
https://github.com/pythonhealthdatascience/stars-reproduce-allen-2020
abstract: >-
This repository forms part of work package 1 on the
NIHR-funded project STARS: Sharing Tools and Artefacts for
Reproducible Simulations. It assesses the computational
reproducibility of: Allen, M., Bhanji, A., Willemsen, J., Dudfield, S.,
Logan, S., & Monks, T. A simulation modelling toolkit for organising
outpatient dialysis services during the COVID-19 pandemic. PLoS One
15, 8 (2020). https://doi.org/10.1371%2Fjournal.pone.0237628.
license: MIT
# Manually update with each GitHub release
version: '0.2.0'
date-released: '2024-06-05'
GitHub Events
Total
Last Year
Committers
Last synced: 9 months ago
Top Committers
| Name | Commits | |
|---|---|---|
| amyheather | a****2@e****k | 162 |
| cffconvert GitHub Action | c****t | 5 |
Committer Domains (Top 20 + Academic)
Dependencies
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- continuumio/miniconda3 latest build