In statistics and machine learning, there’s a tradeoff between precision and recall: tune a system to be more selective and you inevitably miss more true positives. Cancer clinical trials have stumbled into a similar trap. As oncology has shifted from tumor-type-centered studies to gene-directed approaches, eligibility criteria have grown exquisitely precise. Instead of enrolling patients…