Cross Section Uncertainty Quantification

Cross Section Uncertainty Quantification is a methodological framework within cross section data analysis that characterizes and quantifies the statistical reliability and variability of cross-sectional estimates to account for measurement errors, sampling biases, and model assumptions inherent in observational or experimental data.

27

Publications

1.6K

Citations

99

Authors

61

Institutions

Publications per year

2017–2026

6

Authors

99

  1. RS
    R. S. Thorne

    University College London, United Kingdom

    3 publications · 778 citations

    3

    h-index

  2. NO
    Naohiko Otuka

    International Atomic Energy Agency, Austria

    2 publications · 142 citations

    2

    h-index

  3. TS
    Torbjörn Sjöstrand

    Lund University, Sweden

    2 publications · 761 citations

    2

    h-index

  4. RM
    R. McNulty

    University of Liverpool, United Kingdom

    2 publications · 761 citations

    2

    h-index

  5. SY
    S.A. Yost

    Baylor University, United States

    2 publications · 47 citations

    2

    h-index

1–5 of 99

Venues

  1. Journal of High Energy Physics

    JHEP · 3 publications · 76 citations

    3

    h-index

  2. arXiv (Cornell University)

    Repository · 3 publications · 778 citations

    3

    h-index

  3. Nuclear Data Sheets

    2 publications · 36 citations

    2

    h-index

  4. Nuclear Science and Engineering

    2 publications · 44 citations

    2

    h-index

  5. 1

    h-index

1–5