The institutional significance of Gemini for Science's launch is not that Google DeepMind built capable tools — it is that the lab chose to let external validation arrive simultaneously with the announcement. The two Nature papers published alongside the Google I/O reveal represent a deliberate departure from the demo-first, validate-later pattern that has defined AI-for-science releases since AlphaFold. By anchoring the launch to peer-reviewed benchmarks showing ERA outperforming CDC forecasting, DeepMind has set a precedent that other labs announcing science tools will now be measured against — and most will…