{"id":"W2802935654","doi":"10.5206/uwomj.v86i2.2060","title":"Machine learning in medicine","year":2017,"lang":"en","type":"article","venue":"University of Western Ontario Medical Journal","topic":"Artificial Intelligence in Healthcare and Education","field":"Medicine","cited_by":41,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Health care; Process (computing); Machine learning; Quality (philosophy); Limited resources; Artificial intelligence; Risk analysis (engineering); Medicine","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0007163147,0.00006628213,0.0002599088,0.0001350058,0.0003169121,0.00001023593,0.000254847,0.0001174951,0.003020309],"category_scores_gemma":[0.0006011887,0.0000591143,0.00005067909,0.00003179238,0.0002844245,0.0001399991,0.00005332956,0.0009231456,0.00002174396],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000258937,"about_ca_system_score_gemma":0.0008679334,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.2293934,"about_ca_topic_score_gemma":0.4197484,"domain_scores_codex":[0.9989781,0.00004455207,0.0002486019,0.0001046524,0.0004571674,0.0001669737],"domain_scores_gemma":[0.9990565,0.00006538455,0.0002343379,0.0001650497,0.0001235711,0.0003551925],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001766544,0.0000691464,0.9290165,0.0000178056,0.00001510018,0.0005316777,0.006151886,0.000002381249,0.00002055301,0.00002262241,0.0001911079,0.06378456],"study_design_scores_gemma":[0.0006304753,0.0005479704,0.940343,0.001026164,0.00004868204,0.0006387702,0.002818684,0.0002456784,0.0000496298,0.0002980771,0.05327453,0.00007829048],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9697686,0.0001072882,0.0006316114,0.02353431,0.0003547828,0.00006148165,2.233446e-7,0.000007852597,0.005533887],"genre_scores_gemma":[0.9940713,0.0004161135,0.0001872999,0.000243562,0.0002351082,2.661644e-8,0.000003466598,0.000004193934,0.004838941],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.190355,"threshold_uncertainty_score":0.9978911,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1358704942797526,"score_gpt":0.3813033595545752,"score_spread":0.2454328652748226,"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."}}