{"id":"W3214944786","doi":"10.1017/ice.2021.480","title":"Leveraging implementation science to advance antibiotic stewardship practice and research","year":2021,"lang":"en","type":"article","venue":"Infection Control and Hospital Epidemiology","topic":"Antibiotic Use and Resistance","field":"Immunology and Microbiology","cited_by":57,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; University Health Network","funders":"U.S. Department of Veterans Affairs","keywords":"Stewardship (theology); Content (measure theory); Antibiotic Stewardship; Action (physics); Call to action; Computer science; World Wide Web; Business; Antibiotics; Political science; Microbiology; Advertising; Biology; Mathematics","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":[],"consensus_categories":[],"category_scores_codex":[0.003787224,0.0001261184,0.0003309522,0.0001744472,0.0006964366,0.00003206088,0.00007168747,0.0001344266,0.00003668547],"category_scores_gemma":[0.005826246,0.0001119607,0.0000328671,0.0003701066,0.0007334267,0.0002947009,0.0001274877,0.0003503702,0.00006957907],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000618065,"about_ca_system_score_gemma":0.0001626631,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006894344,"about_ca_topic_score_gemma":0.0001166957,"domain_scores_codex":[0.9975197,0.0009072437,0.0003328755,0.0005785055,0.00005348424,0.0006081638],"domain_scores_gemma":[0.9972115,0.001923618,0.000115347,0.0001885721,0.000480288,0.00008074148],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003408825,0.0003019113,0.5516165,0.0001203494,0.000267482,0.00004821877,0.002018915,0.00007303902,0.268048,0.03861101,0.002954039,0.1355996],"study_design_scores_gemma":[0.002383911,0.001091029,0.9013997,0.00008677539,0.00006609615,0.0003409555,0.002486364,0.00005213964,0.01430767,0.00203078,0.07543048,0.0003241388],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9692181,0.00882187,0.004510632,0.0152048,0.0009420994,0.0003329751,0.000008232314,0.00004466474,0.0009166402],"genre_scores_gemma":[0.9958127,0.001244767,0.0005636119,0.002055522,0.00006736832,0.000007402755,0.000007799735,0.000007969992,0.0002328325],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3497832,"threshold_uncertainty_score":0.6974982,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03474144392191426,"score_gpt":0.3963934432850962,"score_spread":0.361651999363182,"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."}}