The author believes the trained network was repeatedly calibrated over thousands of rounds in the same simulator, so its suspicion scores are highly aligned with who ultimately turns out to be the impostor, whereas the general knowledge brought by the language model offers no advantage in this environment, because the impostors' speech has no obvious anomaly and the only way to see through it is to check statements against who could see that room, but no results show the model can reliably perform that check.