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Machine learning-based global maps of ecological variables and the challenge of assessing them
The recent wave of published global maps of ecological variables has caused as much excitement as it has received criticism. Here we look into the data and methods mostly used for creating these maps, and discuss whether the quality of predicted values can be assessed, globally and locally.
| Autores principales: | , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Nature Publishing Group UK
2022
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9033849/ https://www.ncbi.nlm.nih.gov/pubmed/35459230 http://dx.doi.org/10.1038/s41467-022-29838-9 |
| Sumario: | The recent wave of published global maps of ecological variables has caused as much excitement as it has received criticism. Here we look into the data and methods mostly used for creating these maps, and discuss whether the quality of predicted values can be assessed, globally and locally. |
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