The researchers found that using a cross validated variance estimate, called Prediction Sum of Squares (PRESS), instead of the usual variance estimate can improve the chances of finding the correct model in large samples during model selection. This is because the usual variance estimate relies on certain assumptions that may not hold true in model selection scenarios, leading to errors. By using PRESS, which is more robust to errors, the researchers showed that the probability of selecting the right model increases.