{"id":"W2891885422","doi":"10.1016/j.aohep.2018.07.003","title":"The basis of liver regeneration: A systems biology approach","year":2019,"lang":"en","type":"article","venue":"Annals of Hepatology","topic":"Liver physiology and pathology","field":"Medicine","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Liver Centre; University Health Network; University of Toronto","funders":"","keywords":"Liver regeneration; Regeneration (biology); Medicine; Hepatectomy; Calcineurin; Bioinformatics; Gene expression; Transcription factor; Biology; microRNA; Cell biology; Computational biology; Gene; Internal medicine; Genetics; Surgery; Transplantation","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":[0.001922227,0.0008678223,0.001026747,0.001498176,0.0005673771,0.001815463,0.001001738,0.0005673617,0.001416832],"category_scores_gemma":[0.002041235,0.0003008693,0.001696608,0.001271268,0.001160752,0.001277248,0.001083271,0.001080966,0.0002924532],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00145394,"about_ca_system_score_gemma":0.001713762,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002359346,"about_ca_topic_score_gemma":0.00176959,"domain_scores_codex":[0.9993442,0.0003085202,0.00003253051,0.0001625617,0.0001242359,0.00002796582],"domain_scores_gemma":[0.9989997,0.0006672899,0.0001176841,0.00009941751,0.00007583031,0.00004008121],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0002293628,0.0002137507,0.01804336,0.003099499,0.001976979,0.0004028946,0.0003810809,0.606567,0.04478525,0.2199646,0.003444141,0.100892],"study_design_scores_gemma":[0.00002397046,0.000188796,0.006094823,0.0001762619,0.0002729207,0.0001796638,0.0001404343,0.7833595,0.005308594,0.1915593,0.01263792,0.00005774345],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06635758,0.009293808,0.9102576,0.003518272,0.0001926004,0.0002563473,0.002624225,0.0008157748,0.006683725],"genre_scores_gemma":[0.6107597,0.01194477,0.3708021,0.0006482418,0.0002954062,0.0007813486,0.003301466,0.0001475664,0.001319351],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002359346,"threshold_uncertainty_score":0.01054907,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07099483356508438,"score_gpt":0.3171215435760563,"score_spread":0.2461267100109719,"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."}}