{"id":"W3094108931","doi":"10.1139/gen-2020-0131","title":"Machine learning for precision medicine","year":2020,"lang":"en","type":"review","venue":"Genome","topic":"Bioinformatics and Genomic Networks","field":"Biochemistry, Genetics and Molecular Biology","cited_by":452,"is_retracted":false,"has_abstract":true,"ca_institutions":"Alberta Children's Hospital; University of Calgary","funders":"Canada Research Chairs","keywords":"Precision medicine; Data science; Computer science; Big data; Artificial intelligence; Machine learning; Context (archaeology); Process (computing); Data processing; Data mining; Biology","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002519985,0.0003117468,0.0008408443,0.00004728104,0.00008884188,0.00001734143,0.0003256849,0.0003577686,0.00004689119],"category_scores_gemma":[0.0000831963,0.0002335979,0.0003173303,0.00008663092,0.00004081159,0.0000010609,0.0001940165,0.0002423011,0.00005240906],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002012676,"about_ca_system_score_gemma":0.00009284763,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001816619,"about_ca_topic_score_gemma":0.000001593121,"domain_scores_codex":[0.998783,0.00004280286,0.0004914165,0.000345721,0.00008783452,0.000249231],"domain_scores_gemma":[0.9992343,0.00003274615,0.0002850831,0.0002929419,0.0000379619,0.0001170052],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00001282388,0.000004843496,1.028724e-7,0.002526854,0.0001293747,0.000001152319,0.00002562197,0.00001469428,0.00007671115,0.00004801337,0.001243036,0.9959168],"study_design_scores_gemma":[0.0002250045,0.000378421,1.938737e-7,0.0005285843,0.0002128226,0.00002203267,0.000004660762,0.000112009,0.000001205569,0.00007510066,0.9981856,0.0002543889],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[2.477706e-7,0.9855881,0.01186698,0.00005843338,0.0002327962,0.0007021707,0.00007555824,0.00001381532,0.001461847],"genre_scores_gemma":[0.000007201255,0.9914776,0.0009182415,0.0001347451,0.001622294,0.00007848684,0.003773407,0.00006276063,0.001925241],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9969425,"threshold_uncertainty_score":0.9525846,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02580914043119106,"score_gpt":0.2943982431104052,"score_spread":0.2685891026792142,"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."}}