{"id":"W4288041851","doi":"10.3390/antibiotics11081001","title":"A Time Series Analysis Evaluating Antibiotic Prescription Rates in Long-Term Care during the COVID-19 Pandemic in Alberta and Ontario, Canada","year":2022,"lang":"en","type":"article","venue":"Antibiotics","topic":"Antibiotic Use and Resistance","field":"Immunology and Microbiology","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University Health Network; University of Toronto; Western University; University of Calgary; Alberta Health Services; BC Centre for Disease Control; University of British Columbia; Public Health Ontario; Sunnybrook Health Science Centre; University of Ottawa; Ottawa Hospital","funders":"Ministry of Long-Term Care; University of British Columbia; Ministry of Health, Ontario","keywords":"Medical prescription; Medicine; Pandemic; Azithromycin; Long-term care; Public health; Coronavirus disease 2019 (COVID-19); Pediatrics; Antibiotics; Infectious disease (medical specialty); Internal medicine; Disease","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00246498,0.0005615191,0.0006178766,0.001555506,0.0008796711,0.001160388,0.001723274,0.0006077465,0.001767328],"category_scores_gemma":[0.006402923,0.0003201188,0.0009630779,0.003711747,0.0006254826,0.0003823555,0.0007345579,0.0008161243,0.0001783801],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.02155289,"about_ca_system_score_gemma":0.02039006,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9883839,"about_ca_topic_score_gemma":0.9790208,"domain_scores_codex":[0.9984472,0.0002216931,0.000105952,0.0002189144,0.0005003393,0.0005059065],"domain_scores_gemma":[0.994936,0.000796214,0.001252901,0.0002280652,0.002034872,0.0007518783],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004430963,0.0000906518,0.9860951,0.00007559254,0.0003256866,0.0002610322,0.0005679224,0.005317769,0.0002315983,0.0003425946,0.001662504,0.004586556],"study_design_scores_gemma":[0.00002870693,0.00008525811,0.9835543,0.00003441456,0.00009227677,0.00004640773,0.0008976773,0.01410943,0.00005634083,0.00006185511,0.001008351,0.00002498348],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9922753,0.0006576006,0.0004683794,0.0003207297,0.0000239807,0.00005095553,0.005408718,0.0000208363,0.0007735047],"genre_scores_gemma":[0.9927868,0.0003130991,0.0003418695,0.00006048104,0.0000129383,0.00002631014,0.00541893,0.000005799486,0.00103376],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02155289,"threshold_uncertainty_score":0.1563779,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01227826484495036,"score_gpt":0.2576678433135011,"score_spread":0.2453895784685507,"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."}}