{"id":"W4320507249","doi":"10.2196/43725","title":"Electronic Health Record–Based Absolute Risk Prediction Model for Esophageal Cancer in the Chinese Population: Model Development and External Validation","year":2023,"lang":"en","type":"article","venue":"JMIR Public Health and Surveillance","topic":"Esophageal Cancer Research and Treatment","field":"Medicine","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Medical Research Council; China Postdoctoral Science Foundation; National Natural Science Foundation of China; Cancer Research UK; Wellcome Trust","keywords":"Medicine; Population; Receiver operating characteristic; Predictive modelling; Cohort; Prospective cohort study; Risk assessment; Psychological intervention; Environmental health; Demography; Statistics; Internal medicine; Computer science","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":[0.02605636,0.001253682,0.001397859,0.001743079,0.0005691153,0.001257475,0.002121676,0.0009162051,0.002020743],"category_scores_gemma":[0.0224378,0.0005733469,0.002412257,0.001087831,0.0005468946,0.001037037,0.001421813,0.001703846,0.0004061733],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001771157,"about_ca_system_score_gemma":0.003120475,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03366191,"about_ca_topic_score_gemma":0.01459451,"domain_scores_codex":[0.9965404,0.002112794,0.0002236652,0.0006990365,0.0002542702,0.0001699056],"domain_scores_gemma":[0.9846572,0.01131706,0.0009003331,0.001000851,0.001834277,0.0002902426],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00192587,0.0009303355,0.576447,0.0002542388,0.001827998,0.0003586366,0.0004541541,0.3489031,0.0004319865,0.001849956,0.002646119,0.06397052],"study_design_scores_gemma":[0.0001064298,0.0003394609,0.03729662,0.00004523538,0.0003048081,0.00007827849,0.00006487176,0.9604485,0.0001424252,0.0009172002,0.0002296763,0.00002652752],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9505869,0.0006524784,0.04493289,0.0006192048,0.00006419851,0.0003829186,0.001687749,0.0002391204,0.0008346369],"genre_scores_gemma":[0.9807582,0.0002090688,0.01620916,0.00008135135,0.00002978811,0.0004552822,0.001714661,0.00001648957,0.0005260291],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03366191,"threshold_uncertainty_score":0.1378009,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04356932550809758,"score_gpt":0.3721600416440205,"score_spread":0.3285907161359229,"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."}}