Burnham, K.P. and Anderson, D.R. (2002) Model Selection and Multimodel Inference. A Practical Information-Theoretic Approach. 2nd Edition, Springer-Verlag, New York.
https://caestuaries.opennrm.org/assets/06942155460a79991fdf1b57f641b1b4/application/pdf/burnham_anderson2002.pdf

has been cited by the following article:

• TITLE: Unleashing the Power of Information Theory: Enhancing Accuracy in Modeling Physical Phenomena

  AUTHORS: Boris Menin

  KEYWORDS: Finite Information Quantity, International System of Units, Modelling, Physical Constant, Speed of Sound

  JOURNAL NAME: Journal of Applied Mathematics and Physics, Vol.11 No.3, March 28, 2023

  ABSTRACT: When building a model of a physical phenomenon or process, scientists face an inevitable compromise between the simplicity of the model (qualitative-quantitative set of variables) and its accuracy. For hundreds of years, the visual simplicity of a law testified to the genius and depth of the physical thinking of the scientist who proposed it. Currently, the desire for a deeper physical understanding of the surrounding world and newly discovered physical phenomena motivates researchers to increase the number of variables considered in a model. This direction leads to an increased probability of choosing an inaccurate or even erroneous model. This study describes a method for estimating the limit of measurement accuracy, taking into account the stage of model building in terms of storage, transmission, processing and use of information by the observer. This limit, due to the finite amount of information stored in the model, allows you to select the optimal number of variables for the best reproduction of the observed object and calculate the exact values of the threshold discrepancy between the model and the phenomenon under study in measurement theory. We consider two examples: measurement of the speed of sound and measurement of physical constants.