{"id":"W4313323236","doi":"10.1002/smmd.20220031","title":"Multidisciplinary endeavors make future medicine smart","year":2022,"lang":"en","type":"editorial","venue":"Smart Medicine","topic":"Biomedical and Engineering Education","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Multidisciplinary approach; China; Engineering ethics; Health care; Variety (cybernetics); Medicine; Political science; Sociology; Engineering; Social science; Computer science; Artificial intelligence","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.02137383,0.001375549,0.001213115,0.003357498,0.004502274,0.01943411,0.001979974,0.007671917,0.01732658],"category_scores_gemma":[0.0265929,0.0007878743,0.001366744,0.001597913,0.01106942,0.02117562,0.007547062,0.01713512,0.008770578],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003313015,"about_ca_system_score_gemma":0.01076654,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004288664,"about_ca_topic_score_gemma":0.0009676298,"domain_scores_codex":[0.9863019,0.004587621,0.001138794,0.001463398,0.00553807,0.0009702251],"domain_scores_gemma":[0.9587018,0.01567472,0.002553734,0.003458044,0.009566466,0.01004526],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00009275067,0.0001292717,0.0009538914,0.001684469,0.0001227845,0.000496958,0.005118956,0.000488982,0.002151059,0.1963786,0.5797523,0.21263],"study_design_scores_gemma":[0.00001207421,0.00003270811,0.0002782884,0.000510995,0.00002337427,0.0003377572,0.001258912,0.0001723189,0.0002588892,0.06325797,0.933826,0.00003072103],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"editorial","genre_scores_codex":[0.002193057,0.1160503,0.02600981,0.640479,0.1582307,0.0001869701,0.0001416089,0.0009571404,0.05575136],"genre_scores_gemma":[0.081312,0.1558897,0.05455519,0.2936334,0.3072159,0.0004290222,0.0003759262,0.001066391,0.1055225],"genre_candidate":"editorial","genre_consensus":null,"teacher_disagreement_score":0.02137383,"threshold_uncertainty_score":0.1130369,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006968520808642742,"score_gpt":0.2400274904850779,"score_spread":0.2330589696764352,"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."}}