ArticleScientific data2025
CNSW 1.0: Prefectural Reconstruction of China's Surface Water Resources Using Machine Learning Methods.
Article in Scientific data, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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Who cites it
1 citing paper in PubMed.
- CNSW 1.0: Prefectural Reconstruction of China's Surface Water Resources Using Machine Learning Methods.Scientific data · 2025Article
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Authors and funding
8 authors.
Funding
Abstract
A comprehensive and long-term dataset of prefectural surface water resources is crucial for effective water resources management in China. However, there has been a significant gap in the availability of such datasets, with no existing datasets providing comprehensive long-term coverage. To address this gap, we have developed CNSW 1.0, the first long-term (2000-2020) dataset of prefectural surface water resources in China. Utilizing surface water resources data from official water resources bulletins, we employed 14 advanced machine learning models to reconstruct the CNSW 1.0 dataset. The resulting dataset exhibits high accuracy, with an R
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Registered trials
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