Abstract Details
(2023) Improving Understanding of Dissolved Organic Matter by Using Machine Learning to Predict Stable Carbon Isotope Based on Molecular Abundances
Yi Y, Liu T, Merder J, He C, Bao H, Li P, Li S-L, Shi Q & He D
https://doi.org/10.7185/gold2023.16031
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Poster board in Session 6g, Tuesday 11th July 15:30 - 17:30
Yuanbi Yi
View all 2 abstracts at Goldschmidt2023
View abstracts at 3 conferences in series
Tongcun Liu
Julian Merder View abstracts at 2 conferences in series
Chen He View all 2 abstracts at Goldschmidt2023 View abstracts at 4 conferences in series
Hongyan Bao View abstracts at 2 conferences in series
Penghui Li View all 2 abstracts at Goldschmidt2023 View abstracts at 3 conferences in series
Si-Liang Li View all 2 abstracts at Goldschmidt2023 View abstracts at 10 conferences in series
Quan Shi View all 2 abstracts at Goldschmidt2023 View abstracts at 5 conferences in series
Ding He View all 2 abstracts at Goldschmidt2023 View abstracts at 4 conferences in series
Tongcun Liu
Julian Merder View abstracts at 2 conferences in series
Chen He View all 2 abstracts at Goldschmidt2023 View abstracts at 4 conferences in series
Hongyan Bao View abstracts at 2 conferences in series
Penghui Li View all 2 abstracts at Goldschmidt2023 View abstracts at 3 conferences in series
Si-Liang Li View all 2 abstracts at Goldschmidt2023 View abstracts at 10 conferences in series
Quan Shi View all 2 abstracts at Goldschmidt2023 View abstracts at 5 conferences in series
Ding He View all 2 abstracts at Goldschmidt2023 View abstracts at 4 conferences in series
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