{"id":"W2339722308","doi":"10.1186/s12893-016-0131-8","title":"Debate: what is the best method to monitor surgical performance?","year":2016,"lang":"en","type":"letter","venue":"BMC Surgery","topic":"Advanced Statistical Process Monitoring","field":"Decision Sciences","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Division of Civil, Mechanical and Manufacturing Innovation; Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada; National Science Foundation","keywords":"CUSUM; Medicine; Chart; Funnel plot; Process (computing); Statistics; Computer science; Confidence interval; Internal medicine; Publication bias","routes":{"ca_aff":true,"ca_fund":true,"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":[0.06390639,0.000754097,0.002888861,0.00201221,0.001632141,0.004093284,0.004130203,0.01642074,0.005353012],"category_scores_gemma":[0.3321672,0.0005890134,0.001687323,0.002205884,0.006591417,0.007100038,0.001773116,0.02560461,0.005410971],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004780823,"about_ca_system_score_gemma":0.005838665,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003780835,"about_ca_topic_score_gemma":0.003267046,"domain_scores_codex":[0.9600797,0.02213675,0.00574362,0.002614159,0.008581948,0.0008438429],"domain_scores_gemma":[0.6926092,0.2359201,0.0147135,0.008848831,0.04159475,0.006313616],"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":[0.0005596597,0.0002169443,0.009246014,0.001711432,0.0002773245,0.000629607,0.0006174896,0.0009445299,0.0004048134,0.02791929,0.6234692,0.3340037],"study_design_scores_gemma":[0.00123746,0.001010799,0.01374044,0.0177236,0.0005598486,0.005593446,0.002745758,0.01279155,0.001921101,0.3846386,0.5573941,0.0006432842],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.0003997238,0.007793932,0.00197796,0.9850552,0.003703874,0.00001955741,0.0001009563,0.00003790865,0.0009108311],"genre_scores_gemma":[0.04355628,0.02435782,0.01712531,0.8465661,0.06597102,0.0003313844,0.00020516,0.0001571374,0.001729762],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.06390639,"threshold_uncertainty_score":0.3379733,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1763784860019385,"score_gpt":0.4289956163467832,"score_spread":0.2526171303448447,"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."}}