GeneBench-Pro is a research-level benchmark designed to test whether AI models can handle the judgment-heavy analysis that real-world computational biology requires. It expands on the earlier GeneBench to cover harder, more realistic tasks across genomics, quantitative biology, and translational medicine, capturing the complexity, iterative nature, and ambiguity of scientific research.
The benchmark focuses on higher-order judgments that are difficult to formalize, including handling ambiguity, revising assumptions, choosing the correct analysis path, and knowing when a result is decision-ready. The source notes there have been few convincing assessments of these system-level judgment calls, even as weaknesses in them increasingly constrain overall AI performance.
GeneBench-Pro is designed to avoid common benchmark failure modes. Each problem is built synthetically with a known full causal structure, allowing the complexity of each problem to be tuned. The benchmark is constructed so that reasonable differences in subjective analytical choices still produce accepted numerical results, while ablation studies verify that plausible but incorrect analyses fail. Problem drafts are also audited through detailed trace analyses to check for information leakage and unintended solution pathways.