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{"target":"https://pubannotation.org/docs/sourcedb/PMC/sourceid/7782580","sourcedb":"PMC","sourceid":"7782580","source_url":"https://www.ncbi.nlm.nih.gov/pmc/7782580","text":"evaluate the performance of the classification model50. The ROC is a probability curve that shows the trade-off between the true positive rate (TPR) and false-positive rate (FPR) using different threshold settings. The AUROC provides a measure of separability and demonstrated the discriminative capacity of the classification model. The larger the AUROC, the better the performance of the model is for predicting the true positive ","tracks":[{"project":"LitCovid-sentences","denotations":[{"id":"T275","span":{"begin":56,"end":214},"obj":"Sentence"},{"id":"T276","span":{"begin":215,"end":333},"obj":"Sentence"}],"namespaces":[{"prefix":"_base","uri":"http://pubannotation.org/ontology/tao.owl#"}],"attributes":[{"subj":"T275","pred":"source","obj":"LitCovid-sentences"},{"subj":"T276","pred":"source","obj":"LitCovid-sentences"}]}],"config":{"attribute types":[{"pred":"source","value type":"selection","values":[{"id":"LitCovid-sentences","color":"#c9ec93","default":true}]}]}}