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    • Metadata for Pavlovic et al. - Machine Learning Critical Loads

    Metadata Updated: February 8, 2024

    This is the metadata associated with Pavlovic et al. (2023) entitled "Empirical nitrogen and sulfur critical loads of U.S. tree species and their uncertainties with machine learning" (https://www.sciencedirect.com/science/article/pii/S0048969722063513). It is not EPA data and the data and associated metadata is already publicly available on the journal website.

    This dataset is associated with the following publication: Pavlovic, N., S. Chang, J. Huang, K. Craig, C. Clark, K. Horn, and C. Driscoll. Empirical nitrogen and sulfur critical loads of U.S. tree species and their uncertainties with machine learning. SCIENCE OF THE TOTAL ENVIRONMENT. Elsevier BV, AMSTERDAM, NETHERLANDS, 857: 1-10, (2022).

    Access & Use Information

    Public: This dataset is intended for public access and use. License: See this page for license information.

    Downloads & Resources

    References

    https://doi.org/10.1016/j.scitotenv.2022.159252
    https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10241478

    Dates

    Metadata Created Date February 8, 2024
    Metadata Updated Date February 8, 2024

    Metadata Source

    Harvested from EPA ScienceHub

    Other Data Resources

    Additional Metadata

    Resource Type Dataset
    Metadata Created Date February 8, 2024
    Metadata Updated Date February 8, 2024
    Publisher U.S. EPA Office of Research and Development (ORD)
    Maintainer
    Identifier https://doi.org/10.23719/1530094
    Data Last Modified 2022-10-01
    Public Access Level public
    Bureau Code 020:00
    Schema Version https://project-open-data.cio.gov/v1.1/schema
    Harvest Object Id 37c811b1-fbcd-4aaa-8952-9fe15fbc47e6
    Harvest Source Id 04b59eaf-ae53-4066-93db-80f2ed0df446
    Harvest Source Title EPA ScienceHub
    License https://pasteur.epa.gov/license/sciencehub-license-non-epa-generated.html
    Program Code 020:000
    Publisher Hierarchy U.S. Government > U.S. Environmental Protection Agency > U.S. EPA Office of Research and Development (ORD)
    Related Documents https://doi.org/10.1016/j.scitotenv.2022.159252, https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10241478
    Source Datajson Identifier True
    Source Hash d8aab9242573eb5ecf7394f599e518dd4da57883065996751c0159178a4d9462
    Source Schema Version 1.1

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