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Specificity

Definition
AI-generated

Specificity is the true negative rate in binary classification: TN / (TN + FP)—the fraction of negatives correctly classified as negative.

Topics
Probability and inference
Synonyms
True negative rate
Related
Classification Accuracy Area Under the ROC Curve (AUC) Calibration

Why it matters in GWAS

Polygenic and clinical risk rules at a cutoff affect how many unaffected individuals receive false alarms; specificity quantifies that burden alongside recall and calibration of predicted risk.

Example usage

"At the PRS threshold targeting 5% prevalence in the high-risk bin, specificity remained 0.63 in the African-ancestry holdout."

Classification Accuracy Area Under the ROC Curve (AUC) Calibration Polygenic Risk Score (PRS) Precision Recall
Related-term network

Click any node to open that term page.

Node order. The current term is first. Next come every page linked from Related terms, in the same top-to-bottom order as that list. Then new terms appear in two-hop layers: for each of those direct neighbors (in that same order), their related terms are appended if not already listed. A third pass does the same for two-hop nodes. The walk stops when a fixed maximum number of nodes is reached.

References

  • Cohen J. (1960). A coefficient of agreement for nominal scales. Educ Psychol Meas.
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