{"id":"W3112289729","doi":"10.1016/j.cjca.2020.07.229","title":"Big Data for a Big Problem: How Can We Enhance the Implementation of Perioperative Cardiovascular Guidelines?","year":2020,"lang":"en","type":"letter","venue":"Canadian Journal of Cardiology","topic":"Cardiac, Anesthesia and Surgical Outcomes","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"Queen's University","funders":"","keywords":"Medicine; Perioperative; Scopus; Guideline; Asymptomatic; MEDLINE; Cohort; Disease; Perioperative medicine; Troponin; Intensive care medicine; Internal medicine; Surgery; Myocardial infarction; Pathology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"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":[0.02645246,0.0007727009,0.002220527,0.001764519,0.008128852,0.01124461,0.004027142,0.0540332,0.01180344],"category_scores_gemma":[0.1750239,0.001076439,0.002351249,0.001625701,0.008290771,0.015207,0.006426169,0.06809817,0.004625486],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01109582,"about_ca_system_score_gemma":0.04980054,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03641942,"about_ca_topic_score_gemma":0.06282309,"domain_scores_codex":[0.9703325,0.01249313,0.00344171,0.001695135,0.009442359,0.00259519],"domain_scores_gemma":[0.7231188,0.1744017,0.01266722,0.00526146,0.03324863,0.05130216],"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":[0.00003905029,0.00006295018,0.001694567,0.0001536141,0.00006640449,0.0006795531,0.0004159718,0.0001571043,0.00009455936,0.006326069,0.9678988,0.02241129],"study_design_scores_gemma":[0.0002780526,0.0001180398,0.005443938,0.002265233,0.0001389829,0.001463169,0.003204319,0.002014794,0.0002885326,0.07210287,0.9123818,0.0003002961],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.00006989554,0.0003463028,0.00009395415,0.9967205,0.002372225,0.000003911248,0.00001736812,0.00001038259,0.0003655253],"genre_scores_gemma":[0.002946142,0.0013266,0.0009724404,0.9680247,0.02595462,0.0000373942,0.00004359942,0.00002782693,0.0006666826],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.0540332,"threshold_uncertainty_score":0.1398957,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09569052816280298,"score_gpt":0.3220655122496695,"score_spread":0.2263749840868665,"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."}}