{"id":"W4408098078","doi":"10.1139/cjm-2024-0118","title":"Molecular epidemiology and in silico prediction of ciprofloxacin resistance in <i>Salmonella enterica</i> in Canada, 2017–2022","year":2025,"lang":"en","type":"article","venue":"Canadian Journal of Microbiology","topic":"Salmonella and Campylobacter epidemiology","field":"Agricultural and Biological Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Newfoundland and Labrador Centre for Applied Health Research; Public Health Ontario; Government of Newfoundland and Labrador; University of Calgary; Queen Elizabeth II Health Sciences Centre; University of Alberta; University of Manitoba; Institut National de Santé Publique du Québec; Provincial Laboratory of Public Health; Manitoba Health; BC Centre for Disease Control; Horizon Health Network; Toronto Public Health; Public Health Agency of Canada","funders":"","keywords":"Ciprofloxacin; Salmonella enterica; Salmonella; Biology; In silico; Microbiology; Genetics; Antibiotic resistance; Drug resistance; Gene; Bacteria","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"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":[0.0008383372,0.0005241478,0.0004332619,0.00140229,0.001087811,0.001046981,0.0007791978,0.0004634599,0.001938162],"category_scores_gemma":[0.002877847,0.0003913652,0.00109053,0.001227459,0.0003447577,0.0002001235,0.0004609656,0.0006351359,0.0003713615],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01135262,"about_ca_system_score_gemma":0.021414,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9773329,"about_ca_topic_score_gemma":0.9798252,"domain_scores_codex":[0.9995111,0.00008641752,0.00003222504,0.0001125383,0.00008751184,0.0001702997],"domain_scores_gemma":[0.9989941,0.0001959873,0.0001468132,0.00005052593,0.0004022223,0.0002104645],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003291102,0.00008974423,0.9703445,0.00006561922,0.0002837489,0.0002641425,0.000121518,0.01774641,0.001159601,0.0003327437,0.003133179,0.006129575],"study_design_scores_gemma":[0.0001114699,0.0001201304,0.8446382,0.00006500165,0.0002486754,0.0002914256,0.001163394,0.1470831,0.0009265408,0.0002676269,0.005039501,0.0000449967],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9887891,0.0004521231,0.001206084,0.000470176,0.00001584937,0.00005925188,0.007478741,0.0001274662,0.00140111],"genre_scores_gemma":[0.9877224,0.0002136581,0.001882904,0.00009268337,0.000004857711,0.00001311992,0.00928985,0.00002575406,0.0007547796],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02266705,"threshold_uncertainty_score":0.08236945,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01414270657050946,"score_gpt":0.2113973463685452,"score_spread":0.1972546397980357,"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."}}