{"id":"W4382918571","doi":"10.1017/ice.2023.122","title":"Brave new world: Leveraging artificial intelligence for advancing healthcare epidemiology, infection prevention, and antimicrobial stewardship","year":2023,"lang":"en","type":"article","venue":"Infection Control and Hospital Epidemiology","topic":"Artificial Intelligence in Healthcare and Education","field":"Medicine","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"Hotel Dieu Shaver Health and Rehabilitation Centre; Public Health Ontario; University of Toronto","funders":"","keywords":"Antimicrobial stewardship; Stewardship (theology); Health care; Epidemiology; Infection control; Medicine; Business; Intensive care medicine; Political science; Microbiology; Antibiotic resistance; Pathology; Biology","routes":{"ca_aff":true,"ca_fund":false,"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":["metaresearch","metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.004052787,0.000260916,0.0008673507,0.000502892,0.0004651009,0.00001991015,0.00003930623,0.0003197499,0.00002152046],"category_scores_gemma":[0.01039685,0.0002511949,0.0001821199,0.0004679242,0.0002150308,0.0002253211,0.00003742795,0.0004250064,0.00003496875],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001465678,"about_ca_system_score_gemma":0.0002794182,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009617436,"about_ca_topic_score_gemma":0.003092587,"domain_scores_codex":[0.9966158,0.0005824775,0.001311444,0.0006753192,0.0000643849,0.0007505566],"domain_scores_gemma":[0.9943233,0.004347662,0.0004235188,0.0001982886,0.0003057796,0.0004014953],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0002778129,0.00006520464,0.4704662,0.0002720934,0.00006585047,0.000001525819,0.0004651654,0.0004870215,0.000160666,0.008429035,0.002648394,0.516661],"study_design_scores_gemma":[0.0004607523,0.004272837,0.5495592,0.000473456,0.0002410189,0.0001399314,0.0003849111,0.03994112,0.0006261063,0.3918045,0.01151178,0.0005843212],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6673175,0.0008915874,0.236363,0.09054399,0.002878248,0.001657753,0.00001285865,0.000297849,0.00003727394],"genre_scores_gemma":[0.9890531,0.001844925,0.002076121,0.004823337,0.001625006,0.0001577709,0.00009968378,0.0000300912,0.0002899612],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5160767,"threshold_uncertainty_score":0.999994,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1834194272481682,"score_gpt":0.4532034911122385,"score_spread":0.2697840638640703,"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."}}