Conception and Software Implementation of a Nuclear Data Evaluation Pipeline

Article Properties
  • Language
    English
  • DOI (url)
    10.1016/j.nds.2021.04.007
  • Publication Date
    2021/03/01
  • Journal
    Nuclear Data Sheets
  • Indian UGC (journal)
  • Refrences
    113
  • Citations
    11
  • G. Schnabel
  • H. Sjöstrand
  • J. Hansson
  • D. Rochman
  • A. Koning
  • R. Capote
Cite
Schnabel, G., et al. “Conception and Software Implementation of a Nuclear Data Evaluation Pipeline”. Nuclear Data Sheets, vol. 173, 2021, pp. 239-84, https://doi.org/10.1016/j.nds.2021.04.007.
Schnabel, G., Sjöstrand, H., Hansson, J., Rochman, D., Koning, A., & Capote, R. (2021). Conception and Software Implementation of a Nuclear Data Evaluation Pipeline. Nuclear Data Sheets, 173, 239-284. https://doi.org/10.1016/j.nds.2021.04.007
Schnabel, G., H. Sjöstrand, J. Hansson, D. Rochman, A. Koning, and R. Capote. “Conception and Software Implementation of a Nuclear Data Evaluation Pipeline”. Nuclear Data Sheets 173 (2021): 239-84. https://doi.org/10.1016/j.nds.2021.04.007.
Schnabel G, Sjöstrand H, Hansson J, Rochman D, Koning A, Capote R. Conception and Software Implementation of a Nuclear Data Evaluation Pipeline. Nuclear Data Sheets. 2021;173:239-84.
Journal Categories
Science
Physics
Science
Physics
Nuclear and particle physics
Atomic energy
Radioactivity
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Citations Analysis
Category Category Repetition
Science: Physics6
Technology: Electrical engineering. Electronics. Nuclear engineering: Nuclear engineering. Atomic power4
Science: Physics: Nuclear and particle physics. Atomic energy. Radioactivity3
Technology: Electrical engineering. Electronics. Nuclear engineering3
Technology: Engineering (General). Civil engineering (General)3
Science: Astronomy2
Science: Physics: Geophysics. Cosmic physics2
Science: Chemistry: Physical and theoretical chemistry1
Science: Mathematics: Instruments and machines: Electronic computers. Computer science1
Science: Mathematics1
Science: Physics: Atomic physics. Constitution and properties of matter1
The category Science: Physics 6 is the most commonly referenced area in studies that cite this article. The first research to cite this article was titled G-HyND: a hybrid nuclear data estimator with Gaussian processes and was published in 2021. The most recent citation comes from a 2024 study titled A Nuclear Data Evaluation Pipeline for the Fast Neutron Energy Range – using heteroscedastic Gaussian processes to treat model defects. This article reached its peak citation in 2023, with 5 citations. It has been cited in 10 different journals, 30% of which are open access. Among related journals, the Frontiers in Astronomy and Space Sciences cited this research the most, with 2 citations. The chart below illustrates the annual citation trends for this article.
Citations used this article by year