{"id":"W4321639056","doi":"10.1136/bmjopen-2022-068373","title":"Determinants of implementing artificial intelligence-based clinical decision support tools in healthcare: a scoping review protocol","year":2023,"lang":"en","type":"review","venue":"BMJ Open","topic":"Artificial Intelligence in Healthcare and Education","field":"Medicine","cited_by":53,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"Canadian Institutes of Health Research; Alberta Innovates","keywords":"Medicine; Protocol (science); Health care; Clinical decision support system; Health informatics; Decision support system; Public health; Data science; Alternative medicine; Nursing; Artificial intelligence; Pathology","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.01566876,0.0004231739,0.004271426,0.0004190656,0.0001141891,0.00009480883,0.0007839003,0.0004709878,0.0004075968],"category_scores_gemma":[0.007602101,0.0003474703,0.0006242043,0.001396616,0.00008978196,0.0001875639,0.0005211953,0.0006497233,0.000365533],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002670412,"about_ca_system_score_gemma":0.01317015,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001166229,"about_ca_topic_score_gemma":0.003936768,"domain_scores_codex":[0.9878944,0.0009100565,0.008950857,0.0008738398,0.0006591383,0.0007116766],"domain_scores_gemma":[0.9931179,0.00243777,0.002606015,0.001150534,0.0004015115,0.0002863302],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"systematic_review","study_design_scores_codex":[0.0001232345,0.0001341542,0.0007982761,0.3223156,0.00001034459,0.00004599984,0.00001980792,1.124888e-7,1.184604e-8,0.00002054438,0.0004746101,0.6760573],"study_design_scores_gemma":[0.00005887057,0.0007568873,0.00002496271,0.9129269,0.0002160784,0.00003271604,0.00006083309,0.00005670085,0.00002073552,0.0004369335,0.0850839,0.0003244395],"study_design_candidate":"systematic_review","study_design_consensus":null,"genre_codex":"protocol","genre_gemma":"review","genre_scores_codex":[0.000009454349,0.1985444,0.0001465426,0.0006525796,0.0005687216,0.7998277,0.00003926373,0.00004350437,0.0001678506],"genre_scores_gemma":[0.000001588647,0.6334125,0.001428741,0.0006231783,0.0003509683,0.3639227,0.0001380796,0.00006856005,0.0000536851],"genre_candidate":"protocol","genre_consensus":null,"teacher_disagreement_score":0.6757329,"threshold_uncertainty_score":0.9998977,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.8331756807154658,"score_gpt":0.7302464397631725,"score_spread":0.1029292409522933,"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."}}