In the real world it is not possible to manufacture perfect parts or identical parts.
There will be some variation from part-to-part.
As you have explained - even a variation of the difference in technique of modeling identical geometry results in slightly different mesh.
I explain this to my FEA class as imagining they are a cave spider with no vision.
The only thing they can detect is 1 and 0.
The spider must examine the code of ones and zeros in the order in which they are encountered and build a web (mesh). If the code encountered is not exactly the same - the web will not be exactly the same. As we have seen, if modelers take a different approach to reaching the same end goal (finished solid model) then there might be a slightly different analysis result. The question is, is this difference statistically significant.
Now we go back to the real world and much more variability of material/manufacture enter the equation.
I think in the computer world we have a tendency to lean towards treating problems as pure 2+2=4 math problems.
Averaging results more closely represents the real world than 2+2=4 statements.
If you validate your digital model against real world empirical evidence - my guess is that you will plot variable results and average.