{"id":"W2913462228","doi":"10.1016/j.ebiom.2019.02.007","title":"Hepatocellular carcinoma: H-Prune gene regulatory networks","year":2019,"lang":"en","type":"letter","venue":"EBioMedicine","topic":"Hepatocellular Carcinoma Treatment and Prognosis","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"SickKids Foundation; Hospital for Sick Children","funders":"","keywords":"Hepatocellular carcinoma; Epigenomics; Transcriptome; Liver cancer; Medicine; Cancer; Hepatitis B virus; Hepatitis C virus; Cancer research; Bioinformatics; Internal medicine; Oncology; Biology; DNA methylation; Gene; Virus; Genetics; Virology; Gene expression","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0004162472,0.0003239716,0.0005224703,0.0007806058,0.0005846432,0.001353762,0.0005005932,0.0004872978,0.007960316],"category_scores_gemma":[0.001098117,0.0002230484,0.0006085429,0.001076319,0.0006020261,0.0009610783,0.0008581026,0.0005774687,0.002060332],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006194182,"about_ca_system_score_gemma":0.0006163106,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003483835,"about_ca_topic_score_gemma":0.003719642,"domain_scores_codex":[0.9996006,0.00007992739,0.00001127361,0.0001859541,0.00006009233,0.00006214543],"domain_scores_gemma":[0.9995269,0.0001527157,0.0001119298,0.00004170583,0.00006930667,0.00009747993],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00126571,0.0001606905,0.1171046,0.002861693,0.000924988,0.002409888,0.002664048,0.01830731,0.1239998,0.1449175,0.08042033,0.5049635],"study_design_scores_gemma":[0.0001743347,0.0005265345,0.2070927,0.001020679,0.0008549169,0.004483814,0.002251475,0.08405927,0.02071015,0.314322,0.3642397,0.0002643967],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4686756,0.1436315,0.2169232,0.02021642,0.001889247,0.0003312537,0.02227464,0.004578675,0.1214794],"genre_scores_gemma":[0.9333538,0.01863391,0.01946337,0.002885753,0.0007259593,0.0001455721,0.006979418,0.0003086747,0.01750344],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007960316,"threshold_uncertainty_score":0.02662992,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03958757401207608,"score_gpt":0.2272302682362733,"score_spread":0.1876426942241972,"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."}}