{"id":"W4393120052","doi":"10.2147/ott.s444536","title":"Development and Validation of a Machine Learning-Based Model Used for Predicting Hepatocellular Carcinoma Risk in Patients with Hepatitis B-Related Cirrhosis: A Retrospective Study","year":2024,"lang":"en","type":"article","venue":"OncoTargets and Therapy","topic":"Hepatocellular Carcinoma Treatment and Prognosis","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Medicine; Receiver operating characteristic; Cohort; Retrospective cohort study; Hepatocellular carcinoma; Internal medicine; Concordance; Cirrhosis; Framingham Risk Score","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003457164,0.000210809,0.0003834717,0.0001932057,0.0001067602,0.00002871134,0.0000262314,0.00007394749,0.000009709912],"category_scores_gemma":[0.00001787598,0.0001544111,0.00005075299,0.0001999627,0.00003325329,0.0000773355,0.0000120372,0.0001684742,3.064124e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008909999,"about_ca_system_score_gemma":0.0001097821,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003802305,"about_ca_topic_score_gemma":0.00008776856,"domain_scores_codex":[0.9988156,0.00007093182,0.0003230073,0.0003807515,0.000229307,0.0001804235],"domain_scores_gemma":[0.9995589,0.00005256701,0.0001085878,0.0001055077,0.00009846131,0.00007593073],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0006558691,0.0006705528,0.9875244,0.00009713355,0.0003235954,0.00002114257,0.006738077,0.00005058691,0.00008844025,0.000008258838,8.523469e-7,0.003821105],"study_design_scores_gemma":[0.007864175,0.002938946,0.6292031,0.000141927,0.0001436421,7.469981e-7,0.00007620762,0.3573372,0.002082633,0.00003514483,0.00004668824,0.000129659],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9946252,0.002730387,0.0003717554,0.00003603139,0.00002517912,0.002107289,0.00004010567,0.00005040482,0.00001368169],"genre_scores_gemma":[0.9980598,0.0001531593,0.001301785,0.00000870691,0.000009978051,0.000225901,0.0001706805,0.00004219586,0.00002776546],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3583213,"threshold_uncertainty_score":0.6296701,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02177784244713413,"score_gpt":0.2325506435789691,"score_spread":0.2107728011318349,"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."}}