Evaluation cycles are not synchronized across AI platforms. Each platform runs its own evaluation schedule based on its own infrastructure, data update patterns, and ranker tuning processes. The variance in citation behavior across platforms partly reflects the asynchrony of evaluation cycles.
For IEO Engine deployments, evaluation cycle events are visible as position compressions in search console data and as citation pattern changes in gate logs. Tracking these events provides insight into when each AI platform's evaluation has incorporated recent deployment changes.