The article discusses different ways to choose the best statistical models without needing to specify certain values beforehand. By using a method called Cross-Validation Bayes Factors and a new approach called Geometric Intrinsic Bayes Factors, researchers found a way to make accurate model selections without complex calculations. They discovered that by following a simple rule called the "Bridge Rule," they could determine the right amount of data needed for the Cross-Validation Bayes Factors to work effectively. This method provides a practical and cost-effective way to make informed decisions in Bayesian statistics.