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This content will become publicly available on January 1, 2023

Title: Publishing statistical models: Getting the most out of particle physics experiments
The statistical models used to derive the results of experimental analyses are of incredible scientific value andare essential information for analysis preservation and reuse. In this paper, we make the scientific case for systematically publishing the full statistical models and discuss the technical developments that make this practical. By means of a variety of physics cases -including parton distribution functions, Higgs boson measurements, effective field theory interpretations, direct searches for new physics, heavy flavor physics, direct dark matter detection, world averages, and beyond the Standard Model global fits -we illustrate how detailed information on the statistical modelling can enhance the short- and long-term impact of experimental results.
Authors:
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Award ID(s):
2111244
Publication Date:
NSF-PAR ID:
10327531
Journal Name:
SciPost Physics
Volume:
12
Issue:
1
ISSN:
2542-4653
Sponsoring Org:
National Science Foundation
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