{"id":"W4311276420","doi":"10.1016/j.cll.2022.09.004","title":"Clinical Artificial Intelligence","year":2022,"lang":"en","type":"review","venue":"Clinics in Laboratory Medicine","topic":"Machine Learning in Healthcare","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"U.S. National Library of Medicine; National Institutes of Health; International Business Machines Corporation","keywords":"Computer science; Artificial intelligence; Process (computing); Key (lock); Clinical decision support system; Decision support system","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":[0.00133529,0.0008915997,0.001353779,0.002968658,0.0004122934,0.002328705,0.0009924689,0.001729266,0.02085073],"category_scores_gemma":[0.004345514,0.0002797737,0.000543574,0.002644087,0.001056185,0.001781709,0.00155674,0.002924847,0.008998533],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001190044,"about_ca_system_score_gemma":0.00254995,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001057422,"about_ca_topic_score_gemma":0.002494307,"domain_scores_codex":[0.9992895,0.0002213471,0.00008573892,0.0001113607,0.0002260061,0.00006601297],"domain_scores_gemma":[0.9982527,0.0008928148,0.000184573,0.00009361852,0.0004223122,0.0001539109],"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":[0.00003639136,0.00006049533,0.0001486365,0.006225112,0.00004766481,0.00006792281,0.0000418794,0.00008423781,0.0002231442,0.006275633,0.1399782,0.8468108],"study_design_scores_gemma":[0.00003211142,0.00004876875,0.0005867398,0.006366893,0.00005894518,0.0005791491,0.00003485465,0.00007690497,0.0001338251,0.003660693,0.9884104,0.00001062519],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0001343215,0.9769817,0.000836544,0.003575893,0.002661152,0.00003547049,0.00005701988,0.00003512531,0.0156827],"genre_scores_gemma":[0.003199316,0.9741731,0.001322314,0.006501036,0.004212416,0.00005549526,0.000211516,0.00001253736,0.01031236],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.02085073,"threshold_uncertainty_score":0.06975257,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2825975477447819,"score_gpt":0.5295012547514392,"score_spread":0.2469037070066573,"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."}}