Our findings may help explain mixed field study evidence regarding the effects of target difficulty.
Despite the importance of target setting for firms, prior research offers mixed evidence regarding performance consequences of target difficulty levels.
We argue that target flexibility is associated with both target difficulty and firm performance in the field and therefore can significantly contribute to an understanding of their relationship.
A possible explanation for these conflicting results is that in studies finding a cross-modal AB, one of the targets required a speeded response [27], [29], [30] or incorporated a task-switch due to targets differing in task set, target set, target set size, response set, target difficulty, or target-defining features other than modality [26], [27], [28], [31], [32], [33], [34].
Whereas previous findings of time-locked cross-modal interference may have been caused by some sort of task-switch [26], [27], [28], [31], [32], [33], [34], chances for a task-switch to occur were minimal in the current study as there was no change in task set, target set, target set size, response set, target difficulty, or any target-defining feature other than modality.
Since the performance of different algorithms depends on target difficulty, taking this characterization into account becomes essential for evaluating predictions.
The figures show that for all three levels VORESCORE achieves improvements over the whole TM-score range, i.e. for all levels of target difficulty.
Finally, we describe the assessment setup, which allows to evaluate the performance of the method and its comparison with other prediction and rescoring methods on different levels of target difficulty (family, superfamily and fold level).
The percentage of reinforced sequences tended to decrease, since the difficulty of the task increased across sessions, but tended to stabilize or increase when the same target difficulty was repeated in two consecutive sessions (F8,152 = 57.31, p < 0.0001; Figure 1 figure supplement 1B).
