{"id":"W2469595319","doi":"10.1017/cem.2016.199","title":"P023: Code Resus - using a quality improvement approach to improve health care provider response during resuscitations","year":2016,"lang":"en","type":"article","venue":"Canadian Journal of Emergency Medicine","topic":"Disaster Response and Management","field":"Health Professions","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"University Health Network","funders":"","keywords":"Medicine; Emergency department; Health care; CLARITY; Rapid response team; Medical emergency; Cardiopulmonary resuscitation; Quality management; Intervention (counseling); Quality (philosophy); Nursing; Test (biology); Family medicine; Resuscitation; Emergency medicine; Operations management","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004197108,0.0002460541,0.0005359701,0.0008282194,0.000917562,0.00000569592,0.0004022133,0.00009580618,0.0007257471],"category_scores_gemma":[0.002913283,0.0001641569,0.0001184685,0.0005226829,0.00008161001,0.0002128917,0.00006523136,0.0003677015,0.00002765855],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001951031,"about_ca_system_score_gemma":0.004655376,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.01762727,"about_ca_topic_score_gemma":0.04134453,"domain_scores_codex":[0.9947622,0.001291218,0.002077693,0.000363436,0.0005239087,0.0009814907],"domain_scores_gemma":[0.995528,0.0002231645,0.0009714307,0.0005759999,0.0008174361,0.001883935],"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":[0.01344443,0.000215357,0.008284966,0.004083849,0.0007365585,0.0001827192,0.3968175,0.0001229022,0.1348365,0.005260352,0.4171359,0.01887897],"study_design_scores_gemma":[0.009715412,0.003366157,0.0715153,0.004228591,0.0002137379,0.000008641462,0.2731686,0.00001824606,0.0001530864,0.0006424492,0.6361428,0.0008270131],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9230555,0.00147868,0.007585593,0.04562318,0.01138188,0.002503256,0.0002613549,0.00003068935,0.008079816],"genre_scores_gemma":[0.9746666,0.0001198338,0.001796593,0.00284437,0.002026155,0.0001241792,0.000009412952,0.00008382924,0.01832902],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2190069,"threshold_uncertainty_score":0.9889144,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.214303523592117,"score_gpt":0.4871868916072188,"score_spread":0.2728833680151018,"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."}}