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The paper discusses the increasing complexity of simulation frameworks in scientific computing, particularly those that integrate uncertainty quantification, inverse modeling, optimization, and control, referred to as extended simulation frameworks. It highlights the need for quality assurance and reproducibility in these frameworks to prevent blind trust in potentially incorrect simulation results, which can have significant consequences in engineering and policy decisions. The authors propose a paradigm t

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49fpsgr62v
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