{"id":"W3119135423","doi":"10.1590/1980-265x-tce-2019-0163","title":"IMPLEMENTATION AND PERFORMANCE OF TRACKERS FOR THE DETECTION OF SURGICAL ADVERSE EVENTS","year":2020,"lang":"en","type":"article","venue":"Texto & Contexto - Enfermagem","topic":"Patient Safety and Medication Errors","field":"Health Professions","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"BitTorrent tracker; Adverse effect; Medicine; Medical record; Retrospective cohort study; Emergency medicine; Descriptive statistics; Tracking (education); Medical emergency; Surgery; Internal medicine; Psychology; Statistics; Computer science; Artificial intelligence; Eye tracking","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0103494,0.0002498619,0.0003785511,0.002812929,0.000719448,0.0009093293,0.0006312772,0.0003641456,0.0009863878],"category_scores_gemma":[0.04679937,0.0002216109,0.0005656314,0.002211681,0.0003585681,0.0005798045,0.001028788,0.0003897378,0.0003401547],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002205774,"about_ca_system_score_gemma":0.008743449,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03825782,"about_ca_topic_score_gemma":0.04715012,"domain_scores_codex":[0.9917132,0.002651646,0.001676936,0.0006229282,0.002754476,0.0005808093],"domain_scores_gemma":[0.9441339,0.01171003,0.02397392,0.00220611,0.0152349,0.002741095],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00006558937,0.00007675094,0.9749646,0.000134547,0.00001934267,0.00003583804,0.0009061122,0.00008608249,0.0002580389,0.0000462986,0.0006416434,0.02276512],"study_design_scores_gemma":[0.000007137317,0.0002883495,0.9958235,0.0001452254,0.00001724889,0.00008899073,0.001294114,0.0007028253,0.0004192241,0.00002092254,0.001179311,0.00001323881],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9885727,0.0006750199,0.002410135,0.000481012,0.00006265916,0.0007020536,0.00197379,0.00009118715,0.005031412],"genre_scores_gemma":[0.9952526,0.0003731718,0.00309957,0.00005479992,0.00001390145,0.0001719109,0.0006579697,0.000008025571,0.0003680433],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03825782,"threshold_uncertainty_score":0.07607025,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4889542366924376,"score_gpt":0.5482989136244565,"score_spread":0.05934467693201889,"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."}}