{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.000660659,0.0006769414,0.0009149836,0.0005543533,0.0001397171,0.000008455141,0.0005736494,0.000884796,0.01093819],"category_scores_gemma":[0.0004130091,0.0005377418,0.0001024528,0.0006872093,0.0002755922,0.00004250615,0.0001494736,0.002110471,0.0001686051],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000335985,"about_ca_system_score_gemma":0.0001109753,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001903581,"about_ca_topic_score_gemma":0.00006948211,"domain_scores_codex":[0.9966319,0.00005329337,0.000675469,0.0005764883,0.001448798,0.0006140323],"domain_scores_gemma":[0.9982245,0.0004024246,0.0001052718,0.0007452674,0.00007588361,0.000446667],"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":[0.00001249691,0.00002847742,0.00001803122,0.00112311,0.0001244099,0.0000489308,0.0008168237,0.00005586707,0.0001090356,0.00004217219,0.9918473,0.005773331],"study_design_scores_gemma":[0.0009745916,0.0002668725,0.000272086,0.0005867753,0.0001621067,0.00001319324,0.0005083002,0.0006728811,0.000004827078,0.00009306288,0.9959387,0.0005066296],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"editorial","genre_gemma":"editorial","genre_scores_codex":[0.00006142834,0.007468896,0.0003006146,0.00355681,0.9500688,0.0002986509,0.0000788062,0.001162675,0.0370033],"genre_scores_gemma":[0.0004737662,0.00268886,0.0001904595,0.00006817691,0.9668326,0.0001806643,0.003080805,0.0003640952,0.0261206],"genre_candidate":"editorial","genre_consensus":"editorial","teacher_disagreement_score":0.01676375,"threshold_uncertainty_score":0.9997074,"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."}}