{"id":"W2139122604","doi":"10.1080/21505594.2015.1048958","title":"Virulence factors as predictive tools for drug resistance in Pseudomonas aeruginosa","year":2015,"lang":"en","type":"letter","venue":"Virulence","topic":"Antibiotic Resistance in Bacteria","field":"Biochemistry, Genetics and Molecular Biology","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Pseudomonas aeruginosa; Pathogen; Virulence; Pneumonia; Microbiology; Biology; Drug resistance; Opportunistic pathogen; Human pathogen; Antibiotic resistance; Virulence factor; Antibiotics; Virology; Medicine; Bacteria; Internal medicine; Gene","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":[0.0004459754,0.0007103881,0.0006604474,0.000142877,0.0001066009,0.00016213,0.001223513,0.001186743,0.00003133771],"category_scores_gemma":[0.001210372,0.0006990041,0.0002442758,0.0002100093,0.000398717,0.00003938108,0.0002478599,0.0008759148,0.00005579714],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001926181,"about_ca_system_score_gemma":0.0006066152,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000726311,"about_ca_topic_score_gemma":0.0002012524,"domain_scores_codex":[0.9961887,0.000198342,0.0006703794,0.001479978,0.0005699731,0.0008926174],"domain_scores_gemma":[0.9976004,0.0002371864,0.0004619073,0.001237586,0.0003289681,0.0001339314],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0005855542,0.00005104881,0.001816673,0.0003314005,0.00007951453,0.000110227,0.0001830127,0.000006392171,0.0204296,0.00006156012,0.9761787,0.0001663292],"study_design_scores_gemma":[0.0007101784,0.0002366675,0.001503168,0.0005684856,0.00005291107,0.000008471658,0.0001298253,0.000007522784,0.02971119,0.00137768,0.9646611,0.001032798],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8994397,0.00718651,0.004393177,0.06621686,0.003634057,0.004776948,0.003888325,0.0001831271,0.0102813],"genre_scores_gemma":[0.610368,0.003862348,0.01503128,0.2639081,0.01208694,0.001043077,0.01055135,0.0008864304,0.08226249],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2890717,"threshold_uncertainty_score":0.9995461,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02076858831195402,"score_gpt":0.2689134857892898,"score_spread":0.2481448974773357,"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."}}