{"id":"W4316672979","doi":"10.1002/lci2.66","title":"Development of diagnostic and prognostic molecular biomarkers in hepatocellular carcinoma using machine learning: A systematic review","year":2022,"lang":"en","type":"review","venue":"Liver Cancer International","topic":"Cancer, Lipids, and Metabolism","field":"Biochemistry, Genetics and Molecular Biology","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ontario Institute for Cancer Research; Vector Institute; Princess Margaret Cancer Centre; Toronto General Hospital; University Health Network; University of Toronto","funders":"Toronto General and Western Hospital Foundation","keywords":"Hepatocellular carcinoma; Medicine; Molecular biomarkers; Cochrane Library; MEDLINE; Oncology; Internal medicine; Precision medicine; Bioinformatics; Cancer; Personalized medicine; Systematic review; Meta-analysis; Pathology; Biology","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003393605,0.001162214,0.005392216,0.00731702,0.0002822703,0.001405894,0.001438379,0.001198776,0.003714527],"category_scores_gemma":[0.01226427,0.0004778889,0.003987991,0.008052502,0.0004459054,0.001485297,0.0008212947,0.0007555374,0.000331804],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001851921,"about_ca_system_score_gemma":0.005152714,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003856321,"about_ca_topic_score_gemma":0.007930874,"domain_scores_codex":[0.998394,0.0005345437,0.0004877088,0.0001683172,0.0003474748,0.00006794171],"domain_scores_gemma":[0.9915494,0.006341069,0.001146466,0.00009370178,0.0007650011,0.0001043468],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"systematic_review","study_design_gemma":"systematic_review","study_design_scores_codex":[0.0002092363,0.00002245503,0.0007592021,0.8309563,0.00559085,0.00006863268,0.000061746,0.000291937,0.0001710878,0.0003662262,0.003282707,0.1582195],"study_design_scores_gemma":[0.0003029402,0.000344309,0.00671351,0.8690167,0.06170314,0.0006604843,0.0001638944,0.0005421774,0.0004561218,0.0008979289,0.05913184,0.00006679523],"study_design_candidate":"systematic_review","study_design_consensus":"systematic_review","genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0002153969,0.9993549,0.00007730078,0.0001045327,0.00003276788,0.00003243829,0.00009263345,0.000003495203,0.00008660018],"genre_scores_gemma":[0.003955031,0.9954002,0.0002646746,0.000133374,0.00003577693,0.00006925209,0.00009666093,0.000001681593,0.00004328126],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.00731702,"threshold_uncertainty_score":0.01794732,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03741856913682609,"score_gpt":0.3035064890714514,"score_spread":0.2660879199346253,"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."}}