experimental-design-gate

# Experimental Design Gate ## Define before optimizing Write the biological question, experimental unit, primary endpoint, minimum meaningful effect, intervention/contrast, and falsifiable hypothesis. Distinguish biological from technical replication. ## Audit Check: - material and model-system relevance; - controls, randomization, blocking, blinding, and batch balance; - nesting, repeated measures, pairing, and independence; - sample-size justification using a defensible effect range or simulation; - measurement timing, dynamic range, failure thresholds, and missing-data handling; - whether the planned statistic estimates the biological quantity of interest. ## Decision Return one of: - `Go`: the design can test the claim; - `Revise-and-Go`: named changes are required before proceeding; - `No-Go`: the current materials or design cannot identify the claimed effect. Do not rescue a No-Go by adding omics, enrichment, machine learning, or more figures. State the smallest change that would alter the decision. ## Deliverable Provide a design map, control table, sample-size assumptions, analysis skeleton, failure criteria, and records to preserve. Separate confirmatory endpoints from exploratory measurements.