{"id":"W4392011166","doi":"10.1002/anse.202300058","title":"Antibiotic Resistance Detection in <i>Pseudomonas aeruginosa</i>: Recent Strategies, Advances, and Challenges","year":2024,"lang":"en","type":"article","venue":"Analysis & Sensing","topic":"Antibiotic Resistance in Bacteria","field":"Biochemistry, Genetics and Molecular Biology","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"Research Manitoba","keywords":"Pseudomonas aeruginosa; Antibiotic resistance; Antibiotics; Pyocyanin; Antimicrobial; Medicine; Microbiology; Intensive care medicine; Biology; Bacteria; Biofilm; Quorum sensing","routes":{"ca_aff":true,"ca_fund":true,"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":[],"consensus_categories":[],"category_scores_codex":[0.000267125,0.0001870772,0.0002612747,0.0002086933,0.00006429172,0.0001334221,0.00007014164,0.0001311466,0.0000054275],"category_scores_gemma":[0.00004089859,0.0001846252,0.00008381224,0.0005944451,0.00009468019,0.00002341249,0.00004480321,0.0001175038,0.000003825322],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003765083,"about_ca_system_score_gemma":0.00005382567,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005078732,"about_ca_topic_score_gemma":0.01052878,"domain_scores_codex":[0.9986035,0.0001018499,0.0002798367,0.0006174219,0.0001330733,0.000264369],"domain_scores_gemma":[0.9994716,0.00002963725,0.00006476031,0.0003225991,0.00005883118,0.0000525643],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001888001,0.00004977468,0.002828285,0.0006055313,0.0009225766,0.0002080527,0.0002621957,0.0003068596,0.7145709,0.0004894625,0.0001094382,0.2794581],"study_design_scores_gemma":[0.0009799375,0.000264574,0.071245,0.0008662359,0.001859989,0.0001193681,0.004339344,0.006784852,0.3241101,0.001402021,0.586123,0.001905596],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8548564,0.1398594,0.002650867,0.0004465704,0.000178766,0.0001040847,0.000005515343,0.00003705632,0.001861339],"genre_scores_gemma":[0.9012316,0.09728282,0.001163796,0.00004124638,0.0001100156,3.335761e-7,0.00003980276,0.00002023237,0.0001101383],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5860136,"threshold_uncertainty_score":0.7528796,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01203164795466223,"score_gpt":0.2545864052298156,"score_spread":0.2425547572751534,"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."}}