Adirian (sorry for not noticing your response sooner), the situation is more like: we have a million data points and several models that all fit those points very precisely and all agree very precisely on how to interpolate between those points—but if we try to use them to extrapolate wildly, into regions where in fact we have no way of getting any real data points, they diverge. It also turns out that within the region where we can actually get data—where the models agree—they don’t agree merely by coincidence, but turn out to be mathematically equivalent to one another.
You are welcome to describe this situation by saying that the models “completely and totally contradictory”, but I think that would be pretty eccentric.
(This is of course merely an analogy. I think the reality is even less favourable to your case.)
Adirian (sorry for not noticing your response sooner), the situation is more like: we have a million data points and several models that all fit those points very precisely and all agree very precisely on how to interpolate between those points—but if we try to use them to extrapolate wildly, into regions where in fact we have no way of getting any real data points, they diverge. It also turns out that within the region where we can actually get data—where the models agree—they don’t agree merely by coincidence, but turn out to be mathematically equivalent to one another.
You are welcome to describe this situation by saying that the models “completely and totally contradictory”, but I think that would be pretty eccentric.
(This is of course merely an analogy. I think the reality is even less favourable to your case.)