{"id":"W4390610630","doi":"10.1002/nau.25379","title":"How do we make progress in phenotyping patients with lower urinary tract such as overactive bladder and underactive detrusor, including using urine markers and microbiome data, to personalize therapy? ICI‐RS 2023—Part 2","year":2024,"lang":"en","type":"article","venue":"Neurourology and Urodynamics","topic":"Urinary Bladder and Prostate Research","field":"Medicine","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Medicine; Overactive bladder; Urinary system; Microbiome; Urinary urgency; Urology; Lower urinary tract symptoms; Internal medicine; Bioinformatics; Pathology","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":[0.000277111,0.0003322681,0.000378532,0.0004178763,0.0001964087,0.0001796343,0.0001059941,0.0001572542,0.00003421204],"category_scores_gemma":[0.00004746291,0.0002764555,0.0000277756,0.000386696,0.0003002382,0.0004524025,0.0003635579,0.0007955101,0.000001639389],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006378029,"about_ca_system_score_gemma":0.0001391615,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004668808,"about_ca_topic_score_gemma":0.00002787791,"domain_scores_codex":[0.9979017,0.000210387,0.0002007769,0.0009367956,0.0002374858,0.0005128225],"domain_scores_gemma":[0.9990171,0.0003390729,0.00006082603,0.0002926942,0.00007748516,0.0002128215],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.03444543,0.002604525,0.8440132,0.0009157279,0.001226064,0.009546881,0.004605982,0.00004453769,0.002026918,0.000180212,0.0001692405,0.1002213],"study_design_scores_gemma":[0.007283048,0.01127277,0.9258275,0.0005665582,0.0003625216,0.00596533,0.001265261,0.03000493,0.00002087817,0.0003178787,0.01623951,0.0008738146],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9862346,0.007256767,0.00003572709,0.005115799,0.0001645866,0.0008826565,0.0001457772,0.00003241005,0.0001316962],"genre_scores_gemma":[0.995591,0.003135754,0.0002455036,0.0005407222,0.00007061846,0.0000174535,0.00009635893,0.00006478407,0.0002377677],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.09934744,"threshold_uncertainty_score":0.9999688,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03892676682202187,"score_gpt":0.3243804398171254,"score_spread":0.2854536729951035,"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."}}