# Planted-Signal Worlds

In simulated worlds with a planted, known signal, Claude Opus 5.5, GPT-6.1 Sol, GPT-6.1 Terra and Qwen3-32B were asked whether a forecasting model beats a static benchmark. After Gaussian shocks removed a resampling artifact, the three commercial models claimed predictability in 34%, 16% and 44% of 110 no-signal worlds, all above the nominal 5%; once false-positive rates are matched, an in-sample test with a multiple-testing adjustment detects weak signals about as well as the best agent.

In simulated worlds with a planted, known signal, Claude Opus 5.5, GPT-6.1 Sol, GPT-6.1 Terra and Qwen3-32B were asked whether a forecasting model beats a static benchmark. After Gaussian shocks removed a resampling artifact, the three commercial models claimed predictability in 34%, 16% and 44% of 110 no-signal worlds, all above the nominal 5%; once false-positive rates are matched, an in-sample test with a multiple-testing adjustment detects weak signals about as well as the best agent.