{"id":"W3196780008","doi":"10.2196/29807","title":"Patient-Level Cancer Prediction Models From a Nationwide Patient Cohort: Model Development and Validation","year":2021,"lang":"en","type":"article","venue":"JMIR Medical Informatics","topic":"Machine Learning in Healthcare","field":"Computer Science","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Pohang University of Science and Technology; National Research Foundation; National Research Foundation of Korea; Seoul National University Bundang Hospital","keywords":"Medicine; Cohort; Cancer; Population; Medical emergency; Computer science; Environmental health; Pathology; Internal medicine","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":[],"consensus_categories":[],"category_scores_codex":[0.000229843,0.0001491581,0.0001807218,0.00008295086,0.0001794724,0.0001241829,0.0002317977,0.000170233,0.00004346512],"category_scores_gemma":[0.0001669107,0.0001376729,0.00002634868,0.0002395946,0.00003165738,0.0008775864,0.0003737725,0.000352766,0.00001105199],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001463197,"about_ca_system_score_gemma":0.0009169103,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007845092,"about_ca_topic_score_gemma":0.00004295911,"domain_scores_codex":[0.9973634,0.0000722227,0.000794778,0.0002060714,0.001322525,0.000241015],"domain_scores_gemma":[0.9987133,0.0001092858,0.0002479214,0.000313393,0.0003179777,0.0002981964],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000009135614,0.0001457149,0.0127507,0.0002580005,0.00007759276,0.0000138436,0.1016741,0.0749168,0.000007658316,0.009253537,0.002176484,0.7987164],"study_design_scores_gemma":[0.0002543118,0.00002469628,0.002767898,0.0001585305,0.000005149879,0.000008966897,0.0003036186,0.9923886,0.000391378,0.001956781,0.001599064,0.0001409852],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4196234,0.0000860084,0.5782338,0.0008557151,0.0002555238,0.0002552839,0.00003637486,0.0001216636,0.0005322521],"genre_scores_gemma":[0.71955,0.0001084929,0.2768359,0.002827201,0.00005459907,0.0003084499,0.0002571199,0.00001255912,0.00004566631],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9174718,"threshold_uncertainty_score":0.5614138,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03369389996678447,"score_gpt":0.2956901151380917,"score_spread":0.2619962151713073,"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."}}