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Coupling process-based models with machine learning for the prediction of soil carbon and nitrogen cycling
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DOI：10.1016/j.envsoft.2026.107089.png)
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Abstract
En 中文
1. GNNs identified as critical, underutilized tool for spatial soil modeling 2. Hybrid models systematized into parallel, sequential, and integrated modes 3. Causal AI and foundation models proposed to tackle black-box and data limits
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IF:
4.6
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191
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0
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