New AI model could help UN nuclear watchdog achieve near-perfect uranium enrichment assessment

Researchers tested three machine learning models on simulated gamma spectroscopy data to classify nuclear materials and predict uranium-235 enrichment. The models achieved zero classification errors on benchmark tests, with XGBoost estimating enrichment percentages most accurately. This approach offers inspectors new decision-support tools for verifying compliance with international nonproliferation agreements.

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