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Fertilizer N management can mitigate N₂O emissions but complex soil‐weather conditions modulate the mitigation potential. Conditional inference tree (CIT) is a machine learning method able to untangle complex interactions while providing an interpretable model. The goals of this study were (a) to assess the effect of N fertilizer on N₂O emissions, and to use CIT to identify (b) the main soil‐weather drivers of daily N₂O hot moments and (c) fertilizer management options to mitigate them. The study was conducted in 2 yr in no‐till corn (Zea mays L.) with seven combinations of N source and placement tested. Daily N₂O emissions were measured with vented chambers, and soil temperature and water‐filled pore space (WFPS) were measured near the chambers on the same days of gas sampling. Overall, 2013 was drier with lower N₂O emissions than 2014. Cumulative N₂O losses differed across treatments and …