Thank You to Our Peer Reviewers in 2025

Repository for Publications and Research Data (ETH Zurich) 2026 Open access

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Authors: Enrico Camporeale, Raffaele Marino, Thomas Edward Berger, Yangkang Chen, Doris Folini, Geoffrey Fox, C. John, Xiaofeng Li, Donald Lucas, Daniel O’Malley, Steve Tobias, Markus Reichstein
+4 more john rundle, Chaopeng Shen, Renata Wentzcovitch, Yixin Wen
DOI: 10.3929/ethz-c-000798615
Cited by: 0

Abstract

On behalf of AGU, the scientific community, and the editorial team of Journal of Geophysical Research: Machine Learning and Computation, we extend our sincere gratitude to the reviewers who dedicated their time and expertise to evaluating manuscripts for us in 2025. Scientific research can now be communicated in various ways, yet peer review remains the cornerstone of scholarly publishing. We deeply appreciate the reviewers who devoted hours to reading and providing insightful feedback. The high quality of our published papers is a testament to their commitment to this vital community service.

Fields of Study & Subjects

Scientific Computing and Data Management Machine Learning in Materials Science Academic Publishing and Open Access

Publication details

Journal / source
Repository for Publications and Research Data (ETH Zurich)
Publication date
1 April 2026
Language
EN