Code and data for "Machine Learning and Global-Scale Multifactor Meta-Analysis Coupling Evaluate Context-Dependent Effects of Integrated Rice-Animal Co-culture on Soil Carbon Sequestration, Greenhouse Gases Emission and Agro-Yield"

This dataset contains all data and code used in the meta-analysis and machine learning modeling presented in the paper.Included files:1）data.csv: This file contains the extracted data from the studies involved in the meta-analysis. It is also used for machine learning. 2.）1-model: This is the Python code used for training, evaluating the machine learning model, and conducting SHAP analysis. 3）2-partial dependence plot and interaction: This is the Python code used for the partial dependence plot and interaction figure.4）3-trend simulation: This is the Python code used for the trend simulation using MLP.5）SEM:This is the R code used for the SEM equation.All codes are runnable with the provided datasets.