{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002295048,0.001101826,0.001707055,0.003146141,0.0004654808,0.002079512,0.001433198,0.003087165,0.007601994],"category_scores_gemma":[0.004366816,0.0003352434,0.001091617,0.003058997,0.002376252,0.003299972,0.001505009,0.005783078,0.004599595],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002351939,"about_ca_system_score_gemma":0.002454356,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001377447,"about_ca_topic_score_gemma":0.001516527,"domain_scores_codex":[0.9988247,0.0004285458,0.0001138815,0.0001831508,0.0003809345,0.00006893095],"domain_scores_gemma":[0.9971322,0.00206277,0.0001713319,0.0001309668,0.000387312,0.0001155359],"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":[0.00005665968,0.00005291582,0.0002150822,0.01148034,0.000190864,0.0002057522,0.0001261015,0.001078254,0.000515015,0.07350156,0.09094195,0.8216355],"study_design_scores_gemma":[0.00001241937,0.00004663218,0.0003301718,0.003646162,0.00004439492,0.0005315924,0.00004365441,0.0002262847,0.000172489,0.03729633,0.957621,0.00002887414],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.00008147995,0.9885128,0.001797566,0.004951518,0.001291371,0.00001048853,0.00004412099,0.00003907553,0.003271636],"genre_scores_gemma":[0.002037665,0.9895492,0.001355234,0.00334445,0.001972514,0.00002989189,0.00007175344,0.00001272799,0.001626701],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.007601994,"threshold_uncertainty_score":0.02543122,"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."}}