{"id":"W4406098211","doi":"10.2196/65286","title":"Development of a Prediction Model and Risk Score for Self-Assessment and High-Risk Population Identification in Liver Cancer Screening: Prospective Cohort Study","year":2024,"lang":"en","type":"article","venue":"JMIR Public Health and Surveillance","topic":"Hepatocellular Carcinoma Treatment and Prognosis","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Health Commission of the People's Republic of China; Peking Union Medical College; Chinese Academy of Medical Sciences","keywords":"Medicine; Proportional hazards model; Hazard ratio; Population; Cohort; Internal medicine; Prospective cohort study; Liver cancer; Framingham Risk Score; Risk assessment; Cancer; Cohort study; Demography; Confidence interval; Environmental health; Disease","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":[0.01959426,0.001543697,0.001417396,0.00175785,0.0006714262,0.001541557,0.001311022,0.0008038526,0.001392216],"category_scores_gemma":[0.02495984,0.0006151473,0.003071491,0.001373966,0.0003030638,0.0009161312,0.001230576,0.001705983,0.000382987],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008403491,"about_ca_system_score_gemma":0.003216961,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01361284,"about_ca_topic_score_gemma":0.01058187,"domain_scores_codex":[0.995899,0.002682717,0.0002462885,0.0004992759,0.0004773281,0.0001952275],"domain_scores_gemma":[0.9919968,0.004163644,0.0007771297,0.0008148234,0.001883993,0.0003634486],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0005811037,0.0006473506,0.9690672,0.00007668218,0.001113256,0.0001185952,0.0001799048,0.005176412,0.0001613875,0.0004004793,0.00163655,0.02084109],"study_design_scores_gemma":[0.0008631888,0.003235828,0.5435342,0.0002329415,0.003175038,0.0004872837,0.0007119879,0.4427566,0.000592211,0.002063513,0.002218162,0.0001290638],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9151932,0.0004671009,0.07737947,0.0006106558,0.0002298308,0.001846434,0.003091417,0.0002606441,0.0009210977],"genre_scores_gemma":[0.9396728,0.0003054465,0.05433118,0.00009559579,0.00006353002,0.001808188,0.003136019,0.00002845056,0.0005588108],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01959426,"threshold_uncertainty_score":0.1036255,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05683999855308117,"score_gpt":0.3274176075733916,"score_spread":0.2705776090203104,"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."}}