Mathematical way of identifying wrong suggestions or outliers
what is the best mathematical aproach to dynamically find the best possible threshold value above which i can say that the definition is correct and below which you need to have a look if the classes are correct

First, in general it's clear that there's no way to be certain that an answer is correct or incorrect: for instance if for some reason all the classifiers return the same wrong answer, then the threshold condition is satisfied but the answer is wrong.
Now the only way to find an optimal threshold to decide whether an answer is acceptable is to use a set of labelled examples in order to evaluate the answers of the classifiers.
Why? Because the correctness of the answers cannot be determined by any mathematical formula.
So the goal of the game is to assess to what extent this set of classifiers can be trusted to give a correct answer, and that depends on the threshold. So the threshold is a parameter of the predicting system, and this parameter can be estimated (tuned) based on some validation data. The basic method consists in trying all the possible values for the parameter, evaluate the performance in every case and pick the value which obtains the highest performance. Note that there are many  possible evaluation measures for such a scenario: the measure should be chosen carefully depending on the goal of the system (e.g. is it better to have one false positive answer or false negative?).