A predictive model generates a sequence of future values. For each predicted value, it computes two corresponding scores: a 'proposal score' from a function q and a 'target score' from a function p. The model is designed to operate under the constraint that for any given predicted value, its proposal score must be less than or equal to its target score. Given the following sets of scores for four different predicted values, which set contains a score pair that violates this constraint?

Debugging a Predictive Model Constraint

A machine learning model is designed to ensure that for any predicted future value, $\hat{y}_{i+t}$, a calculated 'quality score' from function q does not exceed a 'probability score' from function p. If for a specific prediction the model calculates a quality score $q(\hat{y}_{i+t}) = 0.9$ and a probability score $p(\hat{y}_{i+t}) = 0.7$, this outcome is valid according to the model's design constraint.