Bayes' theorem shows that even with a high test accuracy, if the disease is rare, a positive result is more likely to be a false alarm. It's about adjusting probability with new evidence, just like debugging a complex system—you start with the base rate of an issue before looking at the error logs. My years in IT architecture taught me that initial conditions dominate the outcome, no matter how precise your tools seem.
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