{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001323025,0.0002830002,0.0003687443,0.0001203031,0.0001526997,0.0001255481,0.0001025415,0.0002275026,0.00000165684],"category_scores_gemma":[0.00002983404,0.0002723628,0.00008052722,0.0002168603,0.0005614384,0.00002509585,0.0002002123,0.0001126563,0.0000018949],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000007330949,"about_ca_system_score_gemma":0.0000304796,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008024722,"about_ca_topic_score_gemma":0.0000581077,"domain_scores_codex":[0.9986486,0.0000738203,0.0003355368,0.0004913175,0.0001216476,0.0003290969],"domain_scores_gemma":[0.9993249,0.00002686255,0.0002296102,0.0002408878,0.00006335438,0.0001144325],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0000948954,0.000117964,0.5597785,0.0002042373,0.0001654955,0.000007683198,0.00007609451,0.000002510477,0.4320488,0.000004150863,0.006430711,0.001068913],"study_design_scores_gemma":[0.001496048,0.0004537182,0.8177766,0.0003624245,0.0001417425,0.00005631867,0.0002214001,0.0003181045,0.1699699,0.00001234958,0.008636404,0.0005549639],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9986056,0.000530352,0.00005250694,0.00008179049,0.0001282582,0.0003735746,0.0001388171,0.00004646148,0.00004264599],"genre_scores_gemma":[0.9813429,0.01736827,0.0004187318,0.00006483976,0.00008343607,0.000001009497,0.0004951941,0.00003412063,0.0001915088],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2620789,"threshold_uncertainty_score":0.9999729,"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."}}