{"id":"W4388288055","doi":"10.3390/antibiotics12111591","title":"Antimicrobial Activities of Aztreonam-Avibactam and Comparator Agents against Enterobacterales Analyzed by ICU and Non-ICU Wards, Infection Sources, and Geographic Regions: ATLAS Program 2016–2020","year":2023,"lang":"en","type":"article","venue":"Antibiotics","topic":"Antibiotic Resistance in Bacteria","field":"Biochemistry, Genetics and Molecular Biology","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"Pfizer (Canada)","funders":"Pfizer","keywords":"Aztreonam; Antimicrobial; Multiple drug resistance; Microbiology; Medicine; Carbapenem; Antibiotic resistance; Ceftazidime/avibactam; Avibactam; Phenotypic screening; Minimum inhibitory concentration; Broth microdilution; Carbapenem-resistant enterobacteriaceae; Biology; Drug resistance; Phenotype; Klebsiella pneumoniae; Antibiotics; Escherichia coli; Imipenem; Genetics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"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":[0.0006779052,0.0002085472,0.0002206975,0.000661457,0.00007787512,0.0002993377,0.0002069415,0.0001078436,0.0009915427],"category_scores_gemma":[0.0008580434,0.00009532897,0.0003962109,0.001174442,0.000114984,0.0003177292,0.0004400329,0.0002233976,0.0002154764],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005418879,"about_ca_system_score_gemma":0.0007741053,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004114978,"about_ca_topic_score_gemma":0.006404334,"domain_scores_codex":[0.9995846,0.00008426943,0.00007110973,0.00007113333,0.0001426451,0.00004620804],"domain_scores_gemma":[0.9992698,0.00006308189,0.0003146539,0.00003048751,0.0002332945,0.0000887881],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.004716075,0.0004839996,0.8939128,0.00043878,0.0002364393,0.0001357665,0.0003301815,0.001653064,0.01561363,0.0002558204,0.004013299,0.07821025],"study_design_scores_gemma":[0.00004053582,0.002166911,0.9799932,0.00005259234,0.0001058405,0.0003214367,0.0002481089,0.001026931,0.006571733,0.00006578338,0.009391769,0.00001517678],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9874484,0.001350439,0.0002912394,0.00009383736,0.00002603701,0.0000518952,0.008482425,0.00003024799,0.002225606],"genre_scores_gemma":[0.9811105,0.001163777,0.0008384473,0.00006660865,0.00002195551,0.00006752036,0.01513297,0.000008589188,0.001589731],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004114978,"threshold_uncertainty_score":0.008182049,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007634697299619176,"score_gpt":0.2498458753094932,"score_spread":0.242211178009874,"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."}}