: Researchers use the FIM to measure how distinguishable models are based on their predictions. In sloppy models, FIM eigenvalues are distributed roughly evenly over many decades.
(Waterfall et al., 2006): Proposes that sloppy models belong to a common "universality class" with eigenvalue spectra that are roughly constant on a logarithmic scale. sloppy
(Gutenkunst et al., 2007): Demonstrates that sloppiness is a universal feature in systems biology, suggesting that modelers should focus on predictions rather than exact parameter values. : Researchers use the FIM to measure how