{"id":"W3120196766","doi":"10.1101/2021.01.14.21249830","title":"Knowledge of and Attitudes on Artificial Intelligence in Healthcare: A Provincial Survey Study of Medical Students","year":2021,"lang":"en","type":"preprint","venue":"medRxiv","topic":"Artificial Intelligence in Healthcare and Education","field":"Medicine","cited_by":46,"is_retracted":false,"has_abstract":true,"ca_institutions":"University Health Network; Institute for Work & Health; Toronto Rehabilitation Institute; University of Toronto","funders":"Division of Undergraduate Education","keywords":"Medical education; Specialty; Acknowledgement; Health care; Psychology; Affect (linguistics); Perception; Variety (cybernetics); Medicine; Computer science; Artificial intelligence; Political science","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.001477842,0.000115211,0.0002640391,0.0009442955,0.001395106,0.001405702,0.0003970445,0.0005081252,0.003128534],"category_scores_gemma":[0.005020654,0.0003503948,0.0002708061,0.001827444,0.0009245711,0.000678972,0.0008511174,0.0007547034,0.0005770673],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002152469,"about_ca_system_score_gemma":0.003063086,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1855149,"about_ca_topic_score_gemma":0.1849895,"domain_scores_codex":[0.9989963,0.0002342411,0.00008529227,0.0001000813,0.0002842647,0.0002997947],"domain_scores_gemma":[0.9947778,0.0009864203,0.00146412,0.0001570998,0.0007666145,0.001847904],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002320777,0.000108178,0.9920182,0.00001528884,0.000006000718,0.0000459208,0.005764922,0.00001962485,0.0001485938,0.00003665416,0.0001891234,0.001624199],"study_design_scores_gemma":[0.000005582094,0.0001027387,0.9881166,0.00001233311,0.00000331248,0.00004005187,0.0109857,0.0001361565,0.0000377688,0.0000180734,0.0005363447,0.000005380251],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9989952,0.00001982181,0.00002132365,0.0001975957,0.000001830589,0.00001132516,0.00009372651,0.000001200217,0.0006579386],"genre_scores_gemma":[0.9995083,0.00004769403,0.00002812257,0.00008251783,0.000002282063,0.00001030923,0.00006751082,9.030655e-7,0.0002523794],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1855149,"threshold_uncertainty_score":0.3688701,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2602005786593575,"score_gpt":0.5080088871698533,"score_spread":0.2478083085104957,"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."}}