{"id":"W2783405732","doi":"10.1161/circoutcomes.117.003561","title":"Improving Temporal Trends in Survival and Neurological Outcomes After Out-of-Hospital Cardiac Arrest","year":2018,"lang":"en","type":"article","venue":"Circulation Cardiovascular Quality and Outcomes","topic":"Cardiac Arrest and Resuscitation","field":"Medicine","cited_by":140,"is_retracted":false,"has_abstract":true,"ca_institutions":"Kingston Health Sciences Centre; Sunnybrook Health Science Centre; St. Michael's Hospital","funders":"National Heart, Lung, and Blood Institute; Scheme for Promotion of Academic and Research Collaboration","keywords":"Medicine; Confidence interval; Targeted temperature management; Odds ratio; Cardiopulmonary resuscitation; Guideline; Automated external defibrillator; Logistic regression; Emergency medicine; Population; Emergency medical services; Survival rate; Internal medicine; Resuscitation; Return of spontaneous circulation","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.00119537,0.0001438748,0.0001499802,0.001048993,0.0003103485,0.0006527636,0.0004166484,0.0003441287,0.00118277],"category_scores_gemma":[0.004190581,0.0001047878,0.0003146449,0.001580884,0.0002373649,0.0006048861,0.0004229796,0.000357863,0.0001239413],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007731753,"about_ca_system_score_gemma":0.001102568,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03550018,"about_ca_topic_score_gemma":0.0456772,"domain_scores_codex":[0.9994557,0.0001066068,0.00006882764,0.000144591,0.00008938221,0.0001348238],"domain_scores_gemma":[0.9964498,0.0005408277,0.001937095,0.000177389,0.0006002442,0.00029469],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00004211132,0.000008665268,0.9984462,0.000007179082,0.00002413533,0.0000191231,0.00004677373,0.00008078478,0.00005304381,0.00002435348,0.0001094,0.001138361],"study_design_scores_gemma":[0.000001290965,0.00002816476,0.9992849,0.000005337033,0.00001292385,0.00004802304,0.0001225973,0.0003089365,0.00003664458,0.0000274654,0.0001218451,0.000001864214],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9973204,0.0003528692,0.0002087008,0.0001905312,0.000009357896,0.000007165218,0.001310041,0.000009920113,0.0005910975],"genre_scores_gemma":[0.998914,0.0001178111,0.0001083086,0.00001976826,0.00001224864,0.000004529303,0.0007530521,0.000001755586,0.00006856881],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03550018,"threshold_uncertainty_score":0.0705871,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03279390784884861,"score_gpt":0.3097193163472731,"score_spread":0.2769254084984245,"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."}}