Researchers have developed a diagnostic tool to evaluate the performance of 'judge gates' in skill optimization. A judge gate is a machine learning model that scores and validates candidate solutions without relying on verifiable rewards. The new diagnostic, called the competence bound, estimates whether a judge gate can accurately distinguish correct from incorrect answers based on its own problem-solving abilities. The tool was tested on real-world optimization runs and found to be effective in predicting which type of error occurs when using a judge gate. --- Why it matters: This matters because it provides a way to pre-deploy and evaluate the performance of judge gates, which are crucial for tasks that require adaptation without automatic verifiers. Engineers can use this diagnostic to determine whether their judge gates are competent enough to make accurate decisions. Source: https://arxiv.org/abs/2608.18719