If a test has high sensitivity but low specificity, which statement best describes false positives and false negatives?

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Understanding how sensitivity and specificity relate to false results is key. High sensitivity means the test correctly identifies most people who have the disease, so there are few false negatives. Low specificity means the test wrongly flags many people without the disease as positive, leading to many false positives. So a test that is highly sensitive but not specific will catch most true cases while producing many false alarms. That description is: many false positives and few false negatives.