{"id":"W4387193702","doi":"10.1017/ash.2023.390","title":"Impact of COVID-19 on healthcare-associated infections in Canadian acute-care hospitals: Interrupted time series (2018–2021)","year":2023,"lang":"en","type":"article","venue":"Antimicrobial Stewardship & Healthcare Epidemiology","topic":"Antibiotic Use and Resistance","field":"Immunology and Microbiology","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Medicine; Pandemic; Emergency medicine; Incidence (geometry); Infection control; Intensive care unit; Confidence interval; Poisson regression; Coronavirus disease 2019 (COVID-19); Internal medicine; Intensive care medicine; Infectious disease (medical specialty); Population; Environmental health; Disease","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.004281151,0.0007975491,0.0009805514,0.002545488,0.0009077827,0.001293418,0.001772731,0.0004943593,0.002232579],"category_scores_gemma":[0.01267063,0.0003591247,0.001414183,0.006094794,0.000573671,0.0005519386,0.00120234,0.001119484,0.0002033882],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01535354,"about_ca_system_score_gemma":0.01726834,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9386544,"about_ca_topic_score_gemma":0.8933113,"domain_scores_codex":[0.9961058,0.0003992102,0.0003915324,0.0006207709,0.00170569,0.0007770062],"domain_scores_gemma":[0.989693,0.001160176,0.004280642,0.0006194636,0.003257122,0.0009896084],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003761046,0.00002995531,0.9909169,0.0001538186,0.0005418166,0.00005985246,0.0003101043,0.001254064,0.00007596318,0.0001844463,0.002205151,0.003891758],"study_design_scores_gemma":[0.000009763159,0.00003589558,0.9963972,0.00004910613,0.00009593668,0.00003886356,0.0001583665,0.001628045,0.00005856901,0.00003045619,0.00148384,0.00001407855],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9231923,0.003151717,0.001236447,0.0007137217,0.00008770802,0.000153591,0.06832523,0.000103424,0.003035819],"genre_scores_gemma":[0.9658527,0.0008975914,0.0009419537,0.0001410836,0.00003953921,0.0001300418,0.03141514,0.00002112617,0.0005609118],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06134558,"threshold_uncertainty_score":0.1234137,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.033890200618101,"score_gpt":0.3554272998158577,"score_spread":0.3215370991977567,"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."}}