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Information functionals allow to quantify the degree of randomness of a givenprobability distribution, either absolutely (through min/max entropyprinciples) or relative to a prescribed reference one. Our primary aim is toanalyze the "minimum information" assumption, which is a classic concept (R.Balian, 1968) in the random matrix theory. We put special emphasis on genericlevel (eigenvalue) spacing distributions and the degree of their randomness, oralternatively - information/organization deficit.

Information functionals and the notion of (un)certainty: RMT - inspired case