{"id":"W2900371717","doi":"10.5489/cuaj.5527","title":"Robotic surgery improves transfusion rate and perioperative outcomes using a broad implementation process and multiple surgeon learning curves","year":2018,"lang":"en","type":"article","venue":"Canadian Urological Association Journal","topic":"Prostate Cancer Diagnosis and Treatment","field":"Medicine","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ottawa Hospital; University of Ottawa","funders":"","keywords":"Perioperative; Learning curve; Medicine; Process (computing); Surgery; General surgery; Computer science","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":true,"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":[0.004510208,0.0002780283,0.0004340774,0.0005671048,0.0004040113,0.001215548,0.000735063,0.0003520442,0.003637571],"category_scores_gemma":[0.01805602,0.000167322,0.0008585369,0.0006295039,0.0006486026,0.001114515,0.001052932,0.0005600986,0.0003735423],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002110208,"about_ca_system_score_gemma":0.005226335,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01258207,"about_ca_topic_score_gemma":0.01794749,"domain_scores_codex":[0.9976432,0.0006691451,0.0002189535,0.0002732451,0.0008868453,0.0003085864],"domain_scores_gemma":[0.9904807,0.002378246,0.004410912,0.0005865865,0.001050331,0.001093312],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.003876475,0.002021204,0.4861575,0.001167073,0.0009207695,0.00008905049,0.0004332421,0.008161215,0.000964636,0.0007706718,0.003203086,0.492235],"study_design_scores_gemma":[0.0009208913,0.006912672,0.9800095,0.0005244671,0.0004721523,0.0003353235,0.0002542283,0.004034974,0.0008695697,0.001061922,0.004544507,0.00005979244],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9800889,0.005237856,0.005470042,0.001868307,0.00007734072,0.0003743009,0.0003860076,0.0002148425,0.006282446],"genre_scores_gemma":[0.9952041,0.00138934,0.002385761,0.0002123468,0.00005716637,0.0001006013,0.0002204481,0.00001571494,0.0004145718],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01258207,"threshold_uncertainty_score":0.02501768,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02296065185087541,"score_gpt":0.2938975618686925,"score_spread":0.2709369100178171,"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."}}