15 citations as recorded by crossref.

1. Finale: impact of the ORCHESTRA/ENCORE programmes on Southern Ocean heat and carbon understanding A. Meijers et al. https://doi.org/10.1098/rsta.2022.0070
2. A machine learning approach to identify upper ocean water masses in the Indian Ocean S. Singh & M. Sapkal https://doi.org/10.1007/s40012-025-00417-9
3. Gaussian Mixture Model-Based Cloud- Phase Estimation From GEO- KOMPSAT-2A Observations D. Kim & D. Shin https://doi.org/10.1109/TGRS.2024.3383888
4. Unsupervised classification identifies coherent thermohaline structures in the Weddell Gyre region D. Jones et al. https://doi.org/10.5194/os-19-857-2023
5. Unsupervised classification of the northwestern European seas based on satellite altimetry data L. Poropat et al. https://doi.org/10.5194/os-20-201-2024
6. Winter sea ice edge shaped by Antarctic Circumpolar Current pathways H. Goosse et al. https://doi.org/10.5194/tc-19-5763-2025
7. Different types of subsurface acoustic ducts in the North Pacific A. Xu et al. https://doi.org/10.1121/10.0039545
8. Unveiling Regional Climate Patterns Through Global Subsurface Ocean Temperature Data: An AI Multi-Layer Analysis Framework C. Radin & V. Nieves https://doi.org/10.1007/s41748-024-00409-w
9. GBM: An Ocean Front Detection Framework Y. Wang et al. https://doi.org/10.1109/TGRS.2026.3660295
10. Characterizing vertical upper ocean temperature structures in the European Arctic through unsupervised machine learning E. Thomas & M. Müller https://doi.org/10.1016/j.ocemod.2022.102092
11. Detection of coherent thermohaline structures over the global ocean using clustering E. Romero et al. https://doi.org/10.1016/j.dsr.2024.104344
12. Novel Approach and Index for Evaluating Harmonic Contributions of Multiple Harmonic Sources Based on Gaussian Mixture Model With Multipoint Harmonic Phasor Measurements C. Wang et al. https://doi.org/10.1109/TPWRD.2025.3647055
13. Sea Ice‐Driven Variability in the Pacific Subantarctic Mode Water Formation Regions R. Sanders et al. https://doi.org/10.1029/2023JC020006
14. Three Types of Antarctic Intermediate Water Revealed by a Machine Learning Approach X. Xia et al. https://doi.org/10.1029/2022GL099445
15. Fine-scale observations reveal distinct frontal phytoplankton communities L. Oms et al. https://doi.org/10.1038/s43247-026-03350-0