Fig. 1 | Scientific Reports

Fig. 1

From: Leveraging explainable AI to predict soil respiration sensitivity and its drivers for climate change mitigation

Fig. 1

Workflow for predicting Q10 sensitivity in soils. Environmental, biochemical, and microbiome variables are used as input features. The Extra Trees Classifier distinguishes between high and low Q10 soils, with SHAP values providing interpretability. Clustering of low-Q10 soils identifies subgroups at higher risk of transitioning to high Q10. The histogram uses a total of 24 bins.

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