{"id":"W2028361935","doi":"10.1186/1471-2288-7-20","title":"Developing algorithms for healthcare insurers to systematically monitor surgical site infection rates","year":2007,"lang":"en","type":"article","venue":"BMC Medical Research Methodology","topic":"Surgical site infection prevention","field":"Medicine","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"GlaxoSmithKline (Canada)","funders":"U.S. Public Health Service; Centers for Disease Control and Prevention; UnitedHealth Group; Sanofi; GlaxoSmithKline; Pfizer","keywords":"Operationalization; Descriptive statistics; Quartile; Health care; Medicine; Computer science; Actuarial science; Database; Data mining; Confidence interval; Statistics; Business","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":[0.01362706,0.001278052,0.0009760435,0.004509334,0.0006704131,0.002414446,0.001931331,0.001097347,0.003701013],"category_scores_gemma":[0.05760754,0.001015642,0.001230298,0.002329323,0.000443176,0.002454447,0.001800365,0.001601598,0.001595025],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00144165,"about_ca_system_score_gemma":0.003008675,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007690944,"about_ca_topic_score_gemma":0.004296442,"domain_scores_codex":[0.9947299,0.001986428,0.000946082,0.00096246,0.001130776,0.0002443706],"domain_scores_gemma":[0.9692904,0.01954132,0.00312102,0.002265427,0.005383749,0.0003980785],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0006271611,0.0007145341,0.1856923,0.0002220458,0.0003802256,0.0001916001,0.000673911,0.1261769,0.003266118,0.009573412,0.01850106,0.6539808],"study_design_scores_gemma":[0.0001412884,0.0001225304,0.01045675,0.00005776425,0.00007307428,0.0001445565,0.0001316431,0.9729789,0.00388321,0.007683043,0.004291809,0.00003536595],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.04393553,0.0001592626,0.9330993,0.0005398307,0.00004135038,0.0008094313,0.000958031,0.01861307,0.00184427],"genre_scores_gemma":[0.1172945,0.00007806442,0.8796546,0.0001088395,0.00002519834,0.0006549011,0.001181942,0.0004421059,0.0005598657],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01362706,"threshold_uncertainty_score":0.07206762,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.5889505602967168,"score_gpt":0.6257357425118332,"score_spread":0.0367851822151164,"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."}}