{"id":"W4229366741","doi":"10.2196/36501","title":"Acceptance, Barriers, and Facilitators to Implementing Artificial Intelligence–Based Decision Support Systems in Emergency Departments: Quantitative and Qualitative Evaluation","year":2022,"lang":"en","type":"article","venue":"JMIR Formative Research","topic":"Artificial Intelligence in Healthcare and Education","field":"Medicine","cited_by":86,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Clinical decision support system; Cronbach's alpha; Likert scale; Unified theory of acceptance and use of technology; Qualitative research; Emergency department; Medical education; Medicine; Decision support system; Medical emergency; Family medicine; Nursing; Computer science; Artificial intelligence; Psychology","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":[0.009936863,0.0001619418,0.0002962668,0.001029237,0.0008690758,0.00006175927,0.0001162137,0.00005817237,0.001143112],"category_scores_gemma":[0.001808943,0.0001567927,0.00004007948,0.001536086,0.0001367069,0.00038518,0.0001994068,0.0005258583,0.00004407527],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008002322,"about_ca_system_score_gemma":0.0006237671,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007774255,"about_ca_topic_score_gemma":0.0004855655,"domain_scores_codex":[0.9948055,0.001582986,0.001023044,0.0004512622,0.001489301,0.0006478887],"domain_scores_gemma":[0.9974043,0.0009893974,0.0001424868,0.000207938,0.0009066685,0.0003491629],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.002211028,0.0003972918,0.02443259,0.0004855953,0.00006904704,0.00001370852,0.6029114,0.0006930746,0.0007626496,0.01047285,0.003960367,0.3535904],"study_design_scores_gemma":[0.0001516875,0.003267696,0.00763932,0.0000988777,0.00001527694,0.000006726065,0.9244866,0.04569549,0.001057,0.01516168,0.002192971,0.0002266083],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.990404,0.0003920063,0.003901719,0.001372054,0.0003540714,0.003143611,0.0001034548,0.00001791971,0.0003112053],"genre_scores_gemma":[0.9964162,0.00006230332,0.0006483622,0.00006541788,0.00003871696,0.002614725,0.0001041863,0.00001541936,0.00003463048],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3533638,"threshold_uncertainty_score":0.99977,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3739204572064789,"score_gpt":0.6068305097361,"score_spread":0.232910052529621,"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."}}