In research settings, false negatives can lead to incorrect conclusions and wasted resources. For example, in drug development, failing to detect a biomarker in preclinical trials could result in the premature discontinuation of potentially effective therapies. Similarly, in environmental monitoring, undetected contaminants could lead to misleading assessments of ecosystem health. To address this, researchers often employ robust validation protocols and replicate studies to confirm findings.
