{"id":"W2893024594","doi":"10.1016/j.cjca.2018.07.181","title":"REDUCING DELAY TO TREATMENT OF ST-ELEVATION MYOCARDIAL INFARCTION WITH THE USE OF SOFTWARE ELECTROCARDIOGRAPHIC INTERPRETATION AND ELECTRONIC TRANSMISSION (SCINET)","year":2018,"lang":"en","type":"article","venue":"Canadian Journal of Cardiology","topic":"ECG Monitoring and Analysis","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"Research Manitoba","funders":"","keywords":"Medicine; Myocardial infarction; Emergency department; Cardiac catheterization; Population; Internal medicine; Cardiology; Gold standard (test); ST elevation; Electrocardiography; Medical emergency; Emergency medicine","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":[0.0006362364,0.0002887576,0.0004125194,0.0006324213,0.0001430647,0.0004575133,0.0003349632,0.0002912076,0.003170735],"category_scores_gemma":[0.00504293,0.0001209646,0.000251588,0.0004471242,0.0001034981,0.0003873447,0.0003217533,0.000650779,0.0003082919],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002365141,"about_ca_system_score_gemma":0.0006864651,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001673371,"about_ca_topic_score_gemma":0.002392936,"domain_scores_codex":[0.9995145,0.0002098945,0.00004866915,0.00005006623,0.0001444266,0.00003259538],"domain_scores_gemma":[0.9974236,0.00148338,0.000434442,0.00009482916,0.0003687051,0.0001949623],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.004451305,0.002318534,0.05843743,0.000319163,0.0001916137,0.0002584119,0.0002289658,0.0033326,0.0159656,0.001138448,0.005600377,0.9077576],"study_design_scores_gemma":[0.00476862,0.03161771,0.7457668,0.0007231807,0.001713835,0.005737134,0.0009266132,0.128935,0.04416469,0.00604911,0.02935431,0.000243103],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9056002,0.004115432,0.07300801,0.003069815,0.0003523494,0.000286816,0.0003792781,0.001869203,0.01131902],"genre_scores_gemma":[0.9580093,0.001167526,0.03824788,0.0005115893,0.0002744681,0.00009000469,0.0002491911,0.00009505004,0.001355112],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003170735,"threshold_uncertainty_score":0.01060712,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01400949506033361,"score_gpt":0.2424275030107705,"score_spread":0.2284180079504369,"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."}}