{"id":"W3094572545","doi":"10.1016/j.jacc.2020.09.229","title":"TCT CONNECT-214 Impact of the COVID-19 Pandemic on Acute Coronary Syndrome and Stroke Volumes in Non-Western Countries","year":2020,"lang":"en","type":"article","venue":"Journal of the American College of Cardiology","topic":"COVID-19 and healthcare impacts","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Centre Hospitalier de l’Université de Montréal","funders":"","keywords":"Medicine; Pandemic; Coronavirus disease 2019 (COVID-19); Acute coronary syndrome; Stroke (engine); 2019-20 coronavirus outbreak; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Cardiology; Emergency medicine; Internal medicine; Virology; Myocardial infarction; Disease","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004593155,0.0002220525,0.0001786656,0.001433303,0.0005549251,0.001762078,0.0003247828,0.0007705475,0.02983833],"category_scores_gemma":[0.00318193,0.0001629201,0.0004169801,0.002153107,0.0002941545,0.000555189,0.001216869,0.000900294,0.004811647],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001262872,"about_ca_system_score_gemma":0.003507419,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.07790294,"about_ca_topic_score_gemma":0.08384897,"domain_scores_codex":[0.99961,0.00008990969,0.00003664507,0.00004310377,0.0001041181,0.0001161306],"domain_scores_gemma":[0.9977568,0.0002225932,0.0004232496,0.00008457213,0.0007497654,0.0007631291],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.0003228359,0.0001287247,0.4551674,0.0003293524,0.0001491196,0.0003816926,0.0003702256,0.0006084901,0.0002980219,0.00399042,0.5053395,0.03291424],"study_design_scores_gemma":[0.00009509498,0.0001043975,0.8497159,0.0003387464,0.00005786264,0.000365257,0.001365233,0.0006269653,0.0002179718,0.0008515074,0.1462355,0.00002545707],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.2879524,0.004679902,0.0008021604,0.05991267,0.005898303,0.000259579,0.4003748,0.0006798909,0.2394404],"genre_scores_gemma":[0.774474,0.005100564,0.001259396,0.01155385,0.00360805,0.0004581891,0.1504577,0.0002587152,0.05282944],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.07790294,"threshold_uncertainty_score":0.154899,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04047822750503916,"score_gpt":0.3631242392646726,"score_spread":0.3226460117596335,"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."}}