Supplementary material to "ML-IAM v1.0: Emulating Integrated Assessment Models With Machine Learning"

2026 Open access

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Authors: Yen Shin, Changyoon Lee, Eunsu Kim, Junho Myung, Kiwoong Park, Jiheun Ha, Min-Young Choi, Bomi Kim, Hyun Wook Ka, Jung-Hun Woo, Alice H. Oh, Haewon McJeon
DOI: 10.5194/egusphere-2025-5305-supplement
Cited by: 0

Abstract

This supplementary information contains extended results for ML-IAM v1.0, including scatter plots comparing ML predictions versus original IAM outputs (Figures S1-S3), temporal trajectory comparisons (Figures S4-S6), and SHAP feature importance analysis (Figures S7-S9).

Fields of Study & Subjects

Explainable Artificial Intelligence (XAI) Data Analysis with R Psychometric Methodologies and Testing

Publication details

Publication date
9 January 2026