A research iteration cycle connects hypothesis, implementation, measurement and interpretation. Each result informs whether to refine the experiment, change direction or investigate a new question.
Automation can shorten the mechanical parts of the cycle and increase the number of useful attempts in a fixed period. The value depends on evidence quality because faster unreliable experiments only increase noise.
