Blurb:: Perform bounds-scaling on response values prior to surrogate emulation

Description::

Particularly in multifidelity methods based on regression solutions at
each level of a model hierarchy, scaling can be an issue since the
magnitude of discrepancy data may decay rapidly and regression solvers
may employ absolute tolerances in places.

By activating \c response_scaling, the set of response data used
for each recovery is scaled to [0,1] based on the minimum value
and range of the data set.  This prevents loss of accuracy due to
imbalances in scale across model levels.

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Examples::
Theory::
Faq::
See_Also::	method-multifidelity_polynomial_chaos, method-multifidelity_function_train
