{"id":"W4409411588","doi":"10.1128/aac.01082-24","title":"Genomics for antimicrobial resistance—progress and future directions","year":2025,"lang":"en","type":"review","venue":"Antimicrobial Agents and Chemotherapy","topic":"Bacterial Identification and Susceptibility Testing","field":"Biochemistry, Genetics and Molecular Biology","cited_by":49,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institute of Infection and Immunity","funders":"National Health and Medical Research Council","keywords":"Genomics; Data sharing; Interoperability; Data science; Workflow; Standardization; Public health; Computer science; Medicine; Biology; World Wide Web; Genome; 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":[0.005509037,0.0008728311,0.001483144,0.00146961,0.0005675966,0.003947068,0.001148727,0.00350383,0.006177912],"category_scores_gemma":[0.005057992,0.0002806061,0.001000184,0.001854618,0.002876732,0.005793863,0.002085082,0.005638277,0.002070797],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001841989,"about_ca_system_score_gemma":0.004989847,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001656371,"about_ca_topic_score_gemma":0.001612182,"domain_scores_codex":[0.9986575,0.0005504713,0.0001080729,0.0001951558,0.0003241496,0.0001646806],"domain_scores_gemma":[0.9921876,0.005056564,0.0004215472,0.0002348545,0.001464733,0.0006346179],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001556823,0.0001372172,0.0009661647,0.01090761,0.0001417456,0.0003202734,0.000437565,0.000988475,0.00203035,0.1049908,0.07586232,0.8030619],"study_design_scores_gemma":[0.00001767397,0.0001382409,0.0008546422,0.006503121,0.00007428404,0.0004941414,0.0004220304,0.0004385573,0.0004295549,0.05956593,0.9310185,0.00004335108],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0003310157,0.9646122,0.001790065,0.02883037,0.001855018,0.0000116324,0.00004738792,0.00006054583,0.002461813],"genre_scores_gemma":[0.003844615,0.984198,0.002122997,0.007027392,0.00205579,0.00001630443,0.00006697427,0.00001465053,0.0006533262],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.006177912,"threshold_uncertainty_score":0.02913493,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01784847004781928,"score_gpt":0.3034830668399185,"score_spread":0.2856345967920993,"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."}}