Attribution Calibration

Attribution Calibration is a methodological framework within attribution analysis that ensures the alignment between attributed contributions and ground-truth causal influences by systematically adjusting for biases and scaling inconsistencies in explanatory outputs.

12

Publications

827

Citations

28

Authors

16

Institutions

Publications per year

2017–2026

3

Authors

28

  1. JM
    Jose Menchero

    University of California, Berkeley, United States

    2 publications · 43 citations

    2

    h-index

  2. PA
    Peter A. Stott

    Met Office, United Kingdom

    2 publications · 55 citations

    2

    h-index

  3. TT
    Tie‐Qiao Tang

    Beihang University, China

    1 publications · 132 citations

    1

    h-index

  4. JH
    Jia He

    Beijing University of Technology, China

    1 publications · 132 citations

    1

    h-index

  5. MS
    Mukund Sundararajan

    Google (United States), United States

    1 publications · 20 citations

    1

    h-index

1–5 of 28

Venues

  1. Annual Review of Psychology

    2 publications · 323 citations

    2

    h-index

  2. SSRN Electronic Journal

    Repository · 1 publications · 20 citations

    1

    h-index

  3. Bulletin of the American Meteorological Society

    BAMS · 1 publications · 18 citations

    1

    h-index

  4. 1

    h-index

  5. Journal of Experimental Social Psychology

    1 publications · 114 citations

    1

    h-index

1–5