= Solution
A good <receiver operating characteristic> rises toward the upper-left corner: many reference-positive loci are detected while few reference-negative loci are accepted. The <area under the ROC curve> summarizes this discrimination over cutoffs. \b[Higher is better in the stated score direction; perfect separation gives one.] The displayed value near 0.86 indicates substantial ranking discrimination against this reference.
The area can also be interpreted as the <probability> that a randomly chosen positive receives a higher score than a randomly chosen negative, with half credit for ties. It does not select a cutoff or demonstrate that most retained calls are correct: those practical questions also depend on prevalence and the relative costs of errors.
\Image[/past-exam-of-the-systems-biology-course-of-the-university-of-cambridge/2024/paper-4-roc-and-precision.png]
{title=The same illustrative classifier viewed through ROC and precision–recall curves at ten percent prevalence}
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