{"id":"W2077106477","doi":"10.6000/1929-6029.2015.04.01.12","title":"Time Profile of Time-Dependent Area Under the ROC Curve for Survival Data","year":2015,"lang":"en","type":"article","venue":"International Journal of Statistics in Medical Research","topic":"Digital Imaging for Blood Diseases","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Receiver operating characteristic; Biomarker; Statistics; Hazard ratio; Sensitivity (control systems); Area under the curve; Value (mathematics); Area under curve; Binary number; Hazard; Measure (data warehouse); Survival analysis; Constant (computer programming); Mathematics; Oncology; Medicine; Internal medicine; Computer science; Data mining; Biology; Confidence interval; Engineering","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.007619655,0.00007569636,0.0001802176,0.0002563655,0.00002768102,0.0001984815,0.005190538,0.00003908922,0.0001335529],"category_scores_gemma":[0.0166104,0.000051905,0.00003484052,0.0002080805,0.0003898373,0.0005002553,0.001335909,0.0004048108,0.00004988389],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001294918,"about_ca_system_score_gemma":0.001803413,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004155092,"about_ca_topic_score_gemma":0.0000200928,"domain_scores_codex":[0.9936118,0.0002594349,0.0005571152,0.0001874923,0.0051351,0.0002491152],"domain_scores_gemma":[0.992399,0.003935952,0.0002024533,0.0003984517,0.002767594,0.0002965564],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000821193,0.002727661,0.002261286,0.00007236862,0.000622685,0.001466733,0.0008374631,0.001455692,0.0001761832,0.1665305,0.6108147,0.2122136],"study_design_scores_gemma":[0.00346553,0.0006283778,0.001327987,0.000427122,0.00001885868,0.000221721,0.0004408582,0.7290958,0.0003268587,0.2532367,0.01060881,0.000201426],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.005446716,0.0003119786,0.9767746,0.01118531,0.001088013,0.0002803957,0.001337882,0.00001175354,0.003563353],"genre_scores_gemma":[0.8764623,0.0002067367,0.1177277,0.0006612094,0.00116981,0.00002769179,0.0003578093,0.00005431688,0.003332449],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8710155,"threshold_uncertainty_score":0.9916731,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1772351554068453,"score_gpt":0.4632251824560452,"score_spread":0.2859900270491999,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}