{"id":"W2295866738","doi":"10.3399/bjgp16x684361","title":"Predicting antibiotic prescription after symptomatic treatment for urinary tract infection: development of a model using data from an RCT in general practice","year":2016,"lang":"en","type":"article","venue":"British Journal of General Practice","topic":"Urinary Tract Infections Management","field":"Medicine","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"Mount Sinai Hospital","funders":"Bundesministerium für Bildung und Forschung","keywords":"Medical prescription; Medicine; Randomized controlled trial; Urinary system; Antibiotics; General practice; Intensive care medicine; Urinary infection; Internal medicine; Family medicine; Microbiology; Nursing","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":[0.1206641,0.00252275,0.004781513,0.002499588,0.0008250523,0.002378435,0.002923704,0.002737276,0.003968076],"category_scores_gemma":[0.1400869,0.001270369,0.008691764,0.001812621,0.001024106,0.002295663,0.002403924,0.003099722,0.0005421416],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002254667,"about_ca_system_score_gemma":0.003171065,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01061619,"about_ca_topic_score_gemma":0.006716388,"domain_scores_codex":[0.9310146,0.06168882,0.002602695,0.002902729,0.001057696,0.0007335062],"domain_scores_gemma":[0.7726499,0.2069654,0.009975486,0.004264567,0.004950085,0.001194627],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.02636398,0.002441292,0.7769032,0.003702859,0.03318409,0.0007371624,0.001743936,0.1041575,0.0004145844,0.001679842,0.003138881,0.04553274],"study_design_scores_gemma":[0.005231915,0.009295935,0.09501191,0.001133883,0.02077828,0.0003746886,0.0007143371,0.8613746,0.0002459422,0.004198849,0.00150939,0.0001301062],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9509544,0.003442749,0.03534183,0.002870126,0.0002201793,0.003648602,0.001892145,0.0002396501,0.001390434],"genre_scores_gemma":[0.9740657,0.0005945619,0.02000277,0.000304843,0.0000570303,0.00306029,0.001406988,0.00002544202,0.0004823142],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1206641,"threshold_uncertainty_score":0.6381405,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08419835941229638,"score_gpt":0.3653515263296797,"score_spread":0.2811531669173833,"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."}}