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False Negative

/fɔːls ˈnɛɡətɪv/noun
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A false negative is an outcome in testing or analysis that wrongly indicates the absence of a condition, substance, or event when it is actually present, often leading to overlooked dangers or missed interventions. In modern contexts like AI diagnostics or medical screening, this error underscores the need for high-sensitivity tools to prevent potentially catastrophic oversights.

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