biostudies-literatureChen GNational Natural Science Foundation of China (National Science Foundation of China)5862https://www.ebi.ac.uk/biostudies/studies/S-EPMC9532422biostudies-literatureUnknown13(1)Reconstructing historical atmospheric oxygen (O₂) levels at finer temporal resolution is a top priority for exploring the evolution of life on Earth. This goal, however, is challenged by gaps in traditionally employed sediment-hosted geochemical proxy data. Here, we propose an independent strategy-machine learning with global mafic igneous geochemistry big data to explore atmospheric oxygenation over the last 4.0 billion years. We observe an overall two-step rise of atmospheric O₂ similar to the published curves derived from independent sediment-hosted paleo-oxybarometers but with a more detailed fabric of O₂ fluctuations superimposed. These additional, shorter-term fluctuations are also consistent with previous but less well-established suggestions of O<suNature communicationsReconstructing Earth's atmospheric oxygenation history using machine learning.PMC953242242050103Zhao MShen JLyons TWAgterberg FCheng QChen GHuang NfalseReconstructing Earth's atmospheric oxygenation history using machine learning.Reconstructing historical atmospheric oxygen (O₂) levels at finer temporal resolution is a top priority for exploring the evolution of life on Earth. This goal, however, is challenged by gaps in traditionally employed sediment-hosted geochemical proxy data. Here, we propose an independent strategy-machine learning with global mafic igneous geochemistry big data to explore atmospheric oxygenation over the last 4.0 billion years. We observe an overall two-step rise of atmospheric O₂ similar to the published curves derived from independent sediment-hosted paleo-oxybarometers but with a more detailed fabric of O₂ fluctuations superimposed. These additional, shorter-term fluctuations are also consistent with previous but less well-established suggestions of O<su2022-01-01T00:00:00Z2022 Oct2025-04-04T09:24:24.404Z2025-04-04T09:24:24.404ZS-EPMC95324223619559310.1038/s41467-022-33388-5