Kappa computation when predicted scores are on a different scale

In a situation where predicted scores are on a completely different scale from the observed scores, kappa computation fails because the range of possible scores is too large. We saw this recently with SGDRegressor which produced scores in the range 1233372304332.22 to 1723509896207.16 when human scores were 1-5.

Few possible solutions:
(1) Do not compute kappa if there is no overlap in range between predicted and observed scores.
(2) Do not compute kappa if the range is greater than certain threshold.

Thoughts?