{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.008647962,0.0009615481,0.001133268,0.001187545,0.0004145052,0.0008576322,0.001134727,0.0009319524,0.001315739],"category_scores_gemma":[0.01280466,0.0004305538,0.00153249,0.0009169705,0.0004081398,0.0006736064,0.0009698097,0.00202173,0.0004516767],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001260276,"about_ca_system_score_gemma":0.00179782,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0236929,"about_ca_topic_score_gemma":0.01232915,"domain_scores_codex":[0.9989098,0.0004990401,0.00008742409,0.0002521227,0.0001412609,0.0001103978],"domain_scores_gemma":[0.991785,0.00521064,0.0005554535,0.0007670892,0.001428194,0.0002535325],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0007519643,0.0007799768,0.1916577,0.0001230424,0.000654868,0.0002435289,0.0001505475,0.7324069,0.0007720438,0.0008168955,0.00349032,0.0681523],"study_design_scores_gemma":[0.00002297412,0.0001154853,0.008769804,0.00001620956,0.00005673983,0.00003649663,0.00002185816,0.9899059,0.0002898843,0.0005178784,0.0002347351,0.00001210749],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9048628,0.0007688325,0.08726884,0.0009569945,0.00008337066,0.0003847645,0.003831486,0.000746788,0.001096206],"genre_scores_gemma":[0.9591547,0.0002441961,0.03548813,0.0001233735,0.00003565138,0.0003549118,0.004080821,0.00002670801,0.0004916014],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0236929,"threshold_uncertainty_score":0.04711002,"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."}}