The Verification Gap: OpenAI's o1 omissions, ER scribe failures, and LLM value infidelity all trace to the same un-audited training-to-deployment pipeline

The OpenAI o1 technical report omits external mathematician verification and the Researcher claims OpenAI ingested ChatGPT logs for o1 pre-training sit alongside AI Scribes Reduce Documentation Time in ERs but Show No Measurable Effect on Patient Throughput and WVS Simulation Records 50%+ Initial Value Failure Across 1,200 LLM Personas. Each case shows a system that asserts capability or consent at training time, then delivers unverified or degraded performance once deployed. The same pattern appears in excess mortality undercounting and the TEAM-Design allocation of replays where no human-AI workflow beats baselines. What links them is not domain but the absence of persistent external audit between model release and real-world measurement.