I am an electrical engineer and not a pro statistician.
I have a classification problem and want to compare two classifiers using Cohence kappa metric.
To calculate the kappa value, the predicted class labels (for each classifier) and the real labels are taken. So each classifier has an independent(!) kappa. Given:
method1: 0.73 (0.719 - 0.734)
method2: 0.75 (0.742 - 0.756)
I also calculate 95% CI with analytical formulas of kappa  wiritten in the parentheses that shows significant superiority of method2. However, the reviewers of my paper are still insisting on using statistical hypothesis test.
I could not find any clear hypothesis test for kappa.
I appreciate if someone helps me (with something like bootstrapping or sharing papers or some ideas).
. J. L. Fleiss, B. Levin, and M. C. Paik, “Statistical methods for rates and proportions,” in Statistical Methods for Rates and Proportions, John Wiley & Sons, Inc., 2003, pp. 598–626