{"id":"W3008736804","doi":"10.1099/acmi.0.000111","title":"Identification and characterization of invasive multi-drug-resistant (MDR) Bacteroides genomospecies in Canada","year":2020,"lang":"en","type":"article","venue":"Access Microbiology","topic":"Bacterial Identification and Susceptibility Testing","field":"Biochemistry, Genetics and Molecular Biology","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Public Health Ontario; Trillium Health Centre; University of Toronto","funders":"","keywords":"Meropenem; Metronidazole; Bacteroides; Microbiology; Penicillin; Drug resistance; Medicine; Antimicrobial drug; Antimicrobial; Antibiotics; Antibiotic resistance; Biology; Bacteria; Genetics","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":[0.0001437044,0.0003522334,0.0003494309,0.001264408,0.001503032,0.0008796586,0.0003956514,0.0003368065,0.0005731999],"category_scores_gemma":[0.0005920866,0.0001902132,0.0002496451,0.001417655,0.0003989241,0.0001364006,0.0006476531,0.0003733893,0.0002187068],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00296914,"about_ca_system_score_gemma":0.005845215,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8111097,"about_ca_topic_score_gemma":0.869503,"domain_scores_codex":[0.9995556,0.00001464663,0.00002160272,0.00008888653,0.0001797382,0.0001395741],"domain_scores_gemma":[0.9994776,0.00002664037,0.00006808658,0.00001552521,0.000262648,0.0001496395],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0005721335,0.0002098275,0.4123804,0.0001943514,0.00005056714,0.005151652,0.006266221,0.0004963988,0.5443316,0.0003476723,0.00104611,0.02895305],"study_design_scores_gemma":[0.00001727405,0.0002073548,0.9643714,0.00005091412,0.00004390231,0.003614655,0.006766008,0.0006319066,0.01458731,0.0000561609,0.009619808,0.00003330782],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.99563,0.0004276109,0.0005257682,0.0001723041,0.0000132605,0.00007884542,0.001579607,0.00001359384,0.001558957],"genre_scores_gemma":[0.9922143,0.0008020828,0.00189064,0.0002044971,0.000008972129,0.00001904875,0.002793463,0.00001570581,0.002051328],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1888903,"threshold_uncertainty_score":0.3800054,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02040257187454205,"score_gpt":0.2350510580375313,"score_spread":0.2146484861629893,"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."}}