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?

No file, test, or entry point is named. Start by locating the kappa computation and reproducing the failure with predicted scores around 1233372304332.22–1723509896207.16 and observed scores of 1–5. Done means an agreed policy is implemented for non-overlapping or excessively large score ranges and the failure is covered by a test.

Written by the indexing model from the issue text.