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2026
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| Online Access: | https://doi.org/10.5281/zenodo.20389932 |
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| _version_ | 1866902251269783552 |
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| author | Mao, Mingjiang Gong |
| author_facet | Mao, Mingjiang Gong |
| contents | <p><span>The input datasets used in this study were obtained from publicly available sources, as described in the article and Supplementary Table S1. This study did not generate a separate field-observation dataset. To support transparency and reproducibility, the Python codes used for data processing, NPP estimation, trajectory analysis, machine learning modeling, and SHAP interpretation have been deposited in the Zenodo repository and are publicly available at: 10.5281/zenodo.20389932</span></p> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_20389932 |
| institution | Zenodo |
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| publishDate | 2026 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | Multimodal Dynamics and Threshold Responses of Net Primary Productivity in a Tropical Mountainous Region: Conservation Effectiveness Assessment Based on the Best-Performing Machine Learning Model Mao, Mingjiang Gong <p><span>The input datasets used in this study were obtained from publicly available sources, as described in the article and Supplementary Table S1. This study did not generate a separate field-observation dataset. To support transparency and reproducibility, the Python codes used for data processing, NPP estimation, trajectory analysis, machine learning modeling, and SHAP interpretation have been deposited in the Zenodo repository and are publicly available at: 10.5281/zenodo.20389932</span></p> |
| title | Multimodal Dynamics and Threshold Responses of Net Primary Productivity in a Tropical Mountainous Region: Conservation Effectiveness Assessment Based on the Best-Performing Machine Learning Model |
| url | https://doi.org/10.5281/zenodo.20389932 |