Development, Evaluation, and Application of Machine Learning Models for Accurate Prediction of Root Uptake of Per- and Polyfluoroalkyl Substances.

MLA

Xiang, Lei, et al. “Development, Evaluation, and Application of Machine Learning Models for Accurate Prediction of Root Uptake of Per- and Polyfluoroalkyl Substances.” Environmental Science & Technology, vol. 57, no. 46, Nov. 2023, pp. 18317–28. EBSCOhost, https://doi.org/10.1021/acs.est.2c09788.

APA

Xiang, L., Qiu, J., Chen, Q.-Q., Yu, P.-F., Liu, B.-L., Zhao, H.-M., Li, Y.-W., Feng, N.-X., Cai, Q.-Y., Mo, C.-H., & Li, Q. X. (2023). Development, Evaluation, and Application of Machine Learning Models for Accurate Prediction of Root Uptake of Per- and Polyfluoroalkyl Substances. Environmental Science & Technology, 57(46), 18317–18328. https://doi.org/10.1021/acs.est.2c09788

Chicago

Xiang, Lei, Jing Qiu, Qian-Qi Chen, Peng-Fei Yu, Bai-Lin Liu, Hai-Ming Zhao, Yan-Wen Li, et al. 2023. “Development, Evaluation, and Application of Machine Learning Models for Accurate Prediction of Root Uptake of Per- and Polyfluoroalkyl Substances.” Environmental Science & Technology 57 (46): 18317–28. doi:10.1021/acs.est.2c09788.