{"id":"W4210476749","doi":"10.3390/microorganisms10020292","title":"Correlation between Phenotypic and In Silico Detection of Antimicrobial Resistance in Salmonella enterica in Canada Using Staramr","year":2022,"lang":"en","type":"article","venue":"Microorganisms","topic":"Antibiotic Resistance in Bacteria","field":"Biochemistry, Genetics and Molecular Biology","cited_by":226,"is_retracted":false,"has_abstract":true,"ca_institutions":"Provincial Laboratory of Public Health; University of Alberta; Queen Elizabeth II Health Sciences Centre; Ste. Anne's Hospital; BC Centre for Disease Control; Horizon Health Network; Public Health Ontario; Public Health Agency of Canada; Toronto Public Health; Saskatchewan Disease Control Laboratory; University of Manitoba","funders":"","keywords":"Salmonella enterica; Salmonella; Broth microdilution; Biology; In silico; Concordance; Antibiotic resistance; Genotype; Genetics; Typing; Drug resistance; Gene; Antimicrobial; Microbiology; Antibiotics; Minimum inhibitory concentration; Bacteria","routes":{"ca_aff":true,"ca_fund":false,"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":[0.002533049,0.0006879347,0.0005432472,0.001620036,0.0007446035,0.001397893,0.0006296212,0.0004364883,0.0008194271],"category_scores_gemma":[0.01107449,0.0004601453,0.0006688614,0.001720948,0.0005235249,0.0003222373,0.0008099238,0.000600115,0.0003490763],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004882914,"about_ca_system_score_gemma":0.005299117,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.7328058,"about_ca_topic_score_gemma":0.8369054,"domain_scores_codex":[0.9965898,0.0005279355,0.0002323128,0.0009005374,0.001430592,0.0003188825],"domain_scores_gemma":[0.9933535,0.002063245,0.001060367,0.000396576,0.002770572,0.000355638],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003538041,0.00003804808,0.964729,0.0001050315,0.0002532786,0.0002129003,0.0003450166,0.005499363,0.01225537,0.0001056842,0.000707316,0.01539517],"study_design_scores_gemma":[0.00001563095,0.0001023814,0.9724163,0.00002782923,0.00009781661,0.000333969,0.0003626744,0.01871173,0.006098418,0.00007305558,0.001719723,0.00004046411],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9924724,0.0002883295,0.002577646,0.000126965,0.000007971517,0.00003598921,0.002906637,0.0001821787,0.001402013],"genre_scores_gemma":[0.9910682,0.0002007172,0.004401352,0.00006610945,0.000003071323,0.00001546704,0.003703621,0.00003387028,0.0005076148],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2671942,"threshold_uncertainty_score":0.5375355,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006159603442279736,"score_gpt":0.199978504873911,"score_spread":0.1938189014316313,"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."}}