Cite
New machine learning-based automatic high-throughput video tracking system for assessing water toxicity using Daphnia Magna locomotory responses
MLA
Jaehoon Kim, et al. “New Machine Learning-Based Automatic High-Throughput Video Tracking System for Assessing Water Toxicity Using Daphnia Magna Locomotory Responses.” Scientific Reports, vol. 13, no. 1, Mar. 2023, pp. 1–13. EBSCOhost, https://doi.org/10.1038/s41598-023-27554-y.
APA
Jaehoon Kim, Hyeonseop Yuk, Byeongwook Choi, MiSuk Yang, SongBum Choi, Kyoung-Jin Lee, Sungjong Lee, & Tae-Young Heo. (2023). New machine learning-based automatic high-throughput video tracking system for assessing water toxicity using Daphnia Magna locomotory responses. Scientific Reports, 13(1), 1–13. https://doi.org/10.1038/s41598-023-27554-y
Chicago
Jaehoon Kim, Hyeonseop Yuk, Byeongwook Choi, MiSuk Yang, SongBum Choi, Kyoung-Jin Lee, Sungjong Lee, and Tae-Young Heo. 2023. “New Machine Learning-Based Automatic High-Throughput Video Tracking System for Assessing Water Toxicity Using Daphnia Magna Locomotory Responses.” Scientific Reports 13 (1): 1–13. doi:10.1038/s41598-023-27554-y.