Attribution of Plastic Sources Using Bayesian Inference: Application to River-Sourced Floating Plastic in the South Atlantic Ocean ...

Data from "Attribution of Plastic Sources Using Bayesian Inference: Application to River-Sourced Floating Plastic in the South Atlantic Ocean." The data consists of: - Lagrangian simulation used for analysis. - Prior probability file for the sources. The repository with the code to run the...

Full description

Bibliographic Details
Format: Dataset
Language:English
Published: Utrecht University 2022
Subjects:
Online Access:https://dx.doi.org/10.24416/uu01-thf29m
https://public.yoda.uu.nl/science/UU01/THF29M.html
id ftdatacite:10.24416/uu01-thf29m
record_format openpolar
spelling ftdatacite:10.24416/uu01-thf29m 2024-09-15T18:36:02+00:00 Attribution of Plastic Sources Using Bayesian Inference: Application to River-Sourced Floating Plastic in the South Atlantic Ocean ... 2022 https://dx.doi.org/10.24416/uu01-thf29m https://public.yoda.uu.nl/science/UU01/THF29M.html en eng Utrecht University https://dx.doi.org/10.24416/UU01-90FO27 Creative Commons Attribution-ShareAlike 4.0 International Public License Open - freely retrievable info:eu-repo/semantics/openAccess https://creativecommons.org/licenses/by-sa/4.0/legalcode Natural Sciences - Earth and related environmental sciences 1.5 yoda Research Data Dataset dataset 2022 ftdatacite https://doi.org/10.24416/uu01-thf29m10.24416/UU01-90FO27 2024-09-02T09:17:24Z Data from "Attribution of Plastic Sources Using Bayesian Inference: Application to River-Sourced Floating Plastic in the South Atlantic Ocean." The data consists of: - Lagrangian simulation used for analysis. - Prior probability file for the sources. The repository with the code to run the analysis can be found at https://github.com/OceanParcels/BayesianAnalysis_SouthAtlantic. ... Dataset South Atlantic Ocean DataCite
institution Open Polar
collection DataCite
op_collection_id ftdatacite
language English
topic Natural Sciences - Earth and related environmental sciences 1.5
yoda
spellingShingle Natural Sciences - Earth and related environmental sciences 1.5
yoda
Attribution of Plastic Sources Using Bayesian Inference: Application to River-Sourced Floating Plastic in the South Atlantic Ocean ...
topic_facet Natural Sciences - Earth and related environmental sciences 1.5
yoda
description Data from "Attribution of Plastic Sources Using Bayesian Inference: Application to River-Sourced Floating Plastic in the South Atlantic Ocean." The data consists of: - Lagrangian simulation used for analysis. - Prior probability file for the sources. The repository with the code to run the analysis can be found at https://github.com/OceanParcels/BayesianAnalysis_SouthAtlantic. ...
format Dataset
title Attribution of Plastic Sources Using Bayesian Inference: Application to River-Sourced Floating Plastic in the South Atlantic Ocean ...
title_short Attribution of Plastic Sources Using Bayesian Inference: Application to River-Sourced Floating Plastic in the South Atlantic Ocean ...
title_full Attribution of Plastic Sources Using Bayesian Inference: Application to River-Sourced Floating Plastic in the South Atlantic Ocean ...
title_fullStr Attribution of Plastic Sources Using Bayesian Inference: Application to River-Sourced Floating Plastic in the South Atlantic Ocean ...
title_full_unstemmed Attribution of Plastic Sources Using Bayesian Inference: Application to River-Sourced Floating Plastic in the South Atlantic Ocean ...
title_sort attribution of plastic sources using bayesian inference: application to river-sourced floating plastic in the south atlantic ocean ...
publisher Utrecht University
publishDate 2022
url https://dx.doi.org/10.24416/uu01-thf29m
https://public.yoda.uu.nl/science/UU01/THF29M.html
genre South Atlantic Ocean
genre_facet South Atlantic Ocean
op_relation https://dx.doi.org/10.24416/UU01-90FO27
op_rights Creative Commons Attribution-ShareAlike 4.0 International Public License
Open - freely retrievable
info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-sa/4.0/legalcode
op_doi https://doi.org/10.24416/uu01-thf29m10.24416/UU01-90FO27
_version_ 1810479227086045184