A suggestion just do 2 independent runs for each point in the calibration curve or double the number of points but with the same degree of polynomial as in the current fit. The statistics go havoc because the low degree of freedom.
You see each parameter in the model has an estimated variation but because there are so many of them compared to the number of points, the variation is quite high. So double the number of points and the statistics
gets back on the track.