{"id":"W4226110159","doi":"10.1038/s43856-022-00094-8","title":"Personalized antibiograms for machine learning driven antibiotic selection","year":2022,"lang":"en","type":"article","venue":"Communications Medicine","topic":"Antibiotic Use and Resistance","field":"Immunology and Microbiology","cited_by":68,"is_retracted":false,"has_abstract":true,"ca_institutions":"Hospital for Sick Children","funders":"National Institute of Allergy and Infectious Diseases; National Institutes of Health","keywords":"Medicine; Antibiotics; Piperacillin; Intensive care medicine; Tazobactam; Medical prescription; Antimicrobial stewardship; Antibiotic resistance; Pseudomonas aeruginosa; Pharmacology; Microbiology; Imipenem; Biology","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":[0.00375171,0.0009630669,0.001193108,0.001024965,0.000321519,0.001077074,0.001117093,0.001184985,0.002493548],"category_scores_gemma":[0.01232867,0.0005992451,0.0007796253,0.0006816659,0.0005090032,0.0008053972,0.0007892091,0.001393924,0.0005892492],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001450393,"about_ca_system_score_gemma":0.001845564,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008777175,"about_ca_topic_score_gemma":0.007863802,"domain_scores_codex":[0.9979739,0.001162554,0.000102096,0.0004452732,0.0001787739,0.0001374067],"domain_scores_gemma":[0.9883273,0.009421007,0.000846444,0.0005381619,0.0005929595,0.0002741546],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003369213,0.0002485774,0.01647808,0.00006455436,0.0001085528,0.00009024848,0.00003933917,0.9215074,0.0006587235,0.001250956,0.003003736,0.05621293],"study_design_scores_gemma":[0.0000131561,0.00002836151,0.0003545391,0.000003645132,0.000005212509,0.000007266307,0.000004095077,0.9979143,0.0001979304,0.001325747,0.0001426647,0.000003098668],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4342656,0.001562402,0.545903,0.004922279,0.0001641918,0.0002585606,0.00323426,0.006009034,0.003680701],"genre_scores_gemma":[0.9331284,0.0001194628,0.06358951,0.0004158161,0.0000860423,0.0001162693,0.001436256,0.00007465461,0.001033604],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008777175,"threshold_uncertainty_score":0.01984119,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03169289898127345,"score_gpt":0.2934846891022257,"score_spread":0.2617917901209522,"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."}}