Datasets and derived summary statistics for "Uncertainty-aware neural emulation reveals climate-resilient maize traits at scale"

This record contains the datasets used to generate, analyze, and support the simulations and results for the study “Uncertainty-aware neural emulation reveals climate-resilient maize traits at scale.” The dataset includes the data used for the analyses and experiments presented in the paper, as well as the large-scale simulation dataset comprising two million APSIM-based crop simulations. These datasets support the development and evaluation of the probabilistic emulator, weather-generation workflow, uncertainty analysis, and downstream discovery and analysis pipeline. This dataset was prepared and organized by Mojdeh Saadati. The broader project was conceived and designed by Baskar Ganapathysubramanian, Carlos Messina, and Soumik Sarkar. Carlos Messina, Juan Panelo, and Gustavo Visentini contributed domain expertise and guidance on emulator-variable selection and simulation design. During peer review, access is restricted to editors and reviewers. Upon acceptance, this record will be made openly available under the same DOI.