Calculate specificity (true negative rate) in crossvalidation in AutoMLPipeline

Hi all,
I am used to calculate sensitivity and specificity in classification problems. Sensitivity is recall, so not a problem, but specificity (true negative) is usually not included in evaluation metrics.
Is it possible to calculate the specificity, or true negative rate, of a ML pipeline from crossvalidate ? I am following the tutorial from GitHub - IBM/AutoMLPipeline.jl: A package that makes it trivial to create and evaluate machine learning pipeline architectures.