What precisely is "indeterminacy" in neutrosophic statistics? In Smarandache 2014, Florentin introduces neutrosophic statistics but I don't get a core part of it.
He says:

We  emphasize,  as  in  neutrosophic  probability,
that indeterminacy is different from randomness. While classical statistics is referring to randomness only,  neutrosophic  statistics  is  referring  to  both  randomness and especially indeterminacy.

He also says:

Neutrosophic  Data  is  the  data  that  contains some indeterminacy.

Something about the indeterminate part of neutrosophic numbers is shown as an interval, although I don't know if there any relation to interval arithmetic here.
However, other examples suggest that the indeterminant part is just a measurement of some 'other' category.
What precisely is "indeterminacy" in neutrosophic statistics?

To me this looks like a sensitivity analysis in classical statistics, repackaged to look like a new paradigm.  In classical statistics if we have missing [indeterminant] data we could use propensity scores, inverse-probability-weights, single imputation, or multiple imputation to account for these missing [indeterminant] values.  Performing several sensitivity analyses would produce a range of values used to account for each missing data point and show how each missing data method impacts the overall conclusions.  This paper is suggesting one assigns an interval to each missing value from the very beginning and call it indeterminant statistics. There may be more details but this is what I have gathered from reading the introduction.
