{"id":"W2941205988","doi":"10.1097/01.ju.0000556825.09468.1a","title":"MP62-02 A NOVEL MACHINE-LEARNING AUGMENTED AUDIO-UROFLOWMETRY – COMPARISON WITH STANDARD UROFLOWMETRY","year":2019,"lang":"en","type":"article","venue":"The Journal of Urology","topic":"Urinary Tract Infections Management","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Medicine; Gold standard (test); Internal medicine","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002596556,0.0006490784,0.0007990017,0.0009696383,0.0002746374,0.001388247,0.000752075,0.001594228,0.01119434],"category_scores_gemma":[0.00548503,0.0002544156,0.0007995318,0.0004701358,0.000352818,0.001036043,0.00109012,0.0008359295,0.002077095],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002868639,"about_ca_system_score_gemma":0.0004231335,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009985832,"about_ca_topic_score_gemma":0.0008972415,"domain_scores_codex":[0.9986598,0.0004726958,0.00009592866,0.0002165215,0.0004870749,0.00006788279],"domain_scores_gemma":[0.9980028,0.0008967247,0.000160312,0.0001989023,0.0005854173,0.0001558043],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.01356176,0.001658607,0.02784224,0.001858195,0.000932957,0.0006059767,0.0001614953,0.01027464,0.07691868,0.0008336051,0.0119351,0.8534167],"study_design_scores_gemma":[0.002994606,0.02750214,0.2696672,0.000981768,0.002245259,0.01188972,0.0005063313,0.4813225,0.1268579,0.002569349,0.07288875,0.0005745512],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6157098,0.02021059,0.3117219,0.003385935,0.005493512,0.002192071,0.006003494,0.007157939,0.02812486],"genre_scores_gemma":[0.8095852,0.003666034,0.1682462,0.001396431,0.00162422,0.0008666933,0.00358609,0.0005057885,0.01052326],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01119434,"threshold_uncertainty_score":0.03744882,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01222582237493567,"score_gpt":0.2663995862017834,"score_spread":0.2541737638268478,"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."}}