Journal article Open Access
{ "inLanguage": { "alternateName": "eng", "@type": "Language", "name": "English" }, "description": "<p>Produced and source files for "Anti-clustering in the national SARS-CoV-2 daily infection counts", 2020, by B. F. Roukema</p>\n\n<ul>\n\t<li>subpoisson-252cf1c.pdf - article in pdf format</li>\n\t<li>WP_C19CCTF_SARSCoV2.dat - Wikipedia COVID-19 Case Count Task Force (C19CCTF) medical cases chart data on national daily SARS-CoV-2 infections in csv format; URLs of the specific versions of the source pages are included</li>\n\t<li>WHO_vs_WP_jumps.dat - plain text table comparing jumpiness of WHO to C19CCTF national case count data</li>\n\t<li>phi_N_full.dat - results: clustering parameter phi_i for full national daily infection counts above a threshold of 50 per day</li>\n\t<li>phi_N_28days.dat - as for phi_N_full.dat, for the least noisy 28-day subsequence for each country</li>\n\t<li>phi_N_14days.dat - as for phi_N_28days.dat, for 14-day subsequences</li>\n\t<li>phi_N_07days.dat - as for phi_N_28days.dat, for 7-day subsequences</li>\n\t<li>subpoisson-252cf1c-git.bundle - git source package that can be unbundled with 'git clone subpoisson-252cf1c-git.bundle' and used for reproducibility: to download data, do calculations, analyse them, plot them and produce the article pdf</li>\n\t<li>subpoisson-252cf1c-arXiv.tar.gz - source package for producing the article pdf, together with the reproducibility package, but without the git history; appropriate for ArXiv</li>\n\t<li>software-252cf1c.tar.gz - this should contain all the software, apart from a minimal POSIX-compatible system, needed for compiling and installing the software used in producing this paper</li>\n</ul>\n\n<p>Associated resources:</p>\n\n<ul>\n\t<li>ArXiv preprints: <a href=\"https://arXiv.org/abs/2007.11779\">arXiv:2007.11779</a></li>\n\t<li>Software Heritage (swh): <a href=\"https://archive.softwareheritage.org/swh:1:dir:fcc9d6b111e319e51af88502fe6b233dc78d5166\">swh:1:dir:fcc9d6b111e319e51af88502fe6b233dc78d5166</a></li>\n <li>Pop-science description: <a href=\"https://codeberg.org/boud/subpoisson/src/branch/subpoisson/README-popular-science.md\">What is noisiness in SARS-CoV-2 daily infection counts?</a></li>\n</ul>\n\n<p>All the materials here are free-licensed, as stated in the individual files and packages.</p>", "license": "https://creativecommons.org/licenses/by/4.0/legalcode", "creator": [ { "affiliation": "Nicolaus Copernicus University", "@id": "https://orcid.org/0000-0002-3772-0250", "@type": "Person", "name": "Roukema, Boudewijn F." } ], "headline": "Anti-clustering in the national SARS-CoV-2 daily infection counts", "image": "https://zenodo.org/static/img/logos/zenodo-gradient-round.svg", "datePublished": "2020-07-23", "url": "https://zenodo.org/record/3951152", "version": "252cf1c", "keywords": [ "COVID-19", "Epidemic curve", "Poisson point process" ], "@context": "https://schema.org/", "identifier": "https://doi.org/10.5281/zenodo.3951152", "@id": "https://doi.org/10.5281/zenodo.3951152", "@type": "ScholarlyArticle", "name": "Anti-clustering in the national SARS-CoV-2 daily infection counts" }
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