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In what scenarios might sensitivity analysis results be unreliable, and how can these issues be mitigated?

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Sensitivity analysis can be unreliable if model assumptions fail, data is inaccurate, or large changes alter the solution. Mitigate these by validating data, using robust models, and testing solution stability.

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