{"id":"W4378782572","doi":"10.2196/34453","title":"Patient Safety of Perioperative Medication Through the Lens of Digital Health and Artificial Intelligence","year":2023,"lang":"en","type":"article","venue":"JMIR Perioperative Medicine","topic":"Patient Safety and Medication Errors","field":"Health Professions","cited_by":32,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Patient safety; Perioperative; Medicine; Psychological intervention; Health care; Medical emergency; Intensive care medicine; Nursing; Surgery","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005910133,0.0006625977,0.0005107307,0.003430277,0.00201774,0.01302671,0.001232543,0.003114307,0.00613307],"category_scores_gemma":[0.01623642,0.0003696777,0.0006961162,0.001191306,0.008772439,0.009614341,0.006298876,0.006061663,0.001041142],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002390871,"about_ca_system_score_gemma":0.005075905,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002280119,"about_ca_topic_score_gemma":0.00228107,"domain_scores_codex":[0.9945028,0.002767339,0.0002583546,0.0003428139,0.001856021,0.0002727426],"domain_scores_gemma":[0.9822372,0.01177883,0.001566805,0.001530785,0.001805808,0.001080602],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001108437,0.0002168106,0.007818468,0.001707262,0.0001996193,0.0009855758,0.007964922,0.002591731,0.001840521,0.3835212,0.0513184,0.5417247],"study_design_scores_gemma":[0.00005106583,0.0002342319,0.00703775,0.004579354,0.0001434937,0.00201401,0.009408114,0.004580521,0.002452519,0.4900166,0.4793357,0.0001465382],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.02527423,0.09630114,0.1337155,0.3998615,0.004888309,0.0001950465,0.0004301336,0.001027721,0.3383065],"genre_scores_gemma":[0.7372823,0.09895179,0.09755205,0.0359093,0.008484961,0.0001977628,0.0002776724,0.0001999986,0.02114424],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01302671,"threshold_uncertainty_score":0.03125614,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1438911821855422,"score_gpt":0.4572732484352827,"score_spread":0.3133820662497405,"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."}}