As mentioned in "Challenge requirements", each team could theoretically submit one prediction per day with a maximum number of 102 predictions. In practice we had only 18 submissions which were used to explore different strategies (e.g., two-steps classification, using weighted learning, exploration of classification strategies based on k-nearest neighbors). These initial analyses were comprehensively described in the BSc thesis of the first author. Soon we realized that all strategies provided results lower or similar to using consensus modeling when fitting RMSE for a regression task. Because of simplicity and less number of fitting parameters (e.g., weighting of individual classes) this strategy was selected to develop the final model.