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Part 1: Document Description
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Citation |
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Title: |
05_Air Pollution and COVID-19 Mortality |
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Identification Number: |
doi:10.7910/DVN/5ZN1UF |
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Distributor: |
Harvard Dataverse |
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Date of Distribution: |
2021-05-26 |
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Version: |
1 |
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Bibliographic Citation: |
Spatial Data Lab, 2021, "05_Air Pollution and COVID-19 Mortality", https://doi.org/10.7910/DVN/5ZN1UF, Harvard Dataverse, V1 |
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Citation |
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Title: |
05_Air Pollution and COVID-19 Mortality |
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Identification Number: |
doi:10.7910/DVN/5ZN1UF |
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Authoring Entity: |
Spatial Data Lab (Spatial Data Lab) |
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Distributor: |
Harvard Dataverse |
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Access Authority: |
Spatial Data Lab |
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Depositor: |
China, Data Lab |
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Date of Deposit: |
2021-05-26 |
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Holdings Information: |
https://doi.org/10.7910/DVN/5ZN1UF |
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Study Scope |
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Keywords: |
Computer and Information Science, Earth and Environmental Sciences, Medicine, Health and Life Sciences, Social Sciences |
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Abstract: |
This is a paper replication using worfklow tool KNIME. The origignal paper is published on Science Advances at https://advances.sciencemag.org/content/6/45/eabd4049. Reference: Wu, X., Nethery, R. C., Sabath, M. B., Braun, D., & Dominici, F. (2020). Air pollution and COVID-19 mortality in the United States: Strengths and limitations of an ecological regression analysis. Science advances, 6(45), eabd4049. |
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Methodology and Processing |
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Sources Statement |
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Data Access |
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Notes: |
<a href="http://creativecommons.org/publicdomain/zero/1.0">CC0 1.0</a> |
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Other Study Description Materials |
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Label: |
05_air_pollution.knwf |
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Notes: |
application/octet-stream |