{"id":"W3124927206","doi":"10.1111/echo.14962","title":"The COVID‐19 Worsening Score (COWS)—a predictive bedside tool for critical illness","year":2021,"lang":"en","type":"article","venue":"Echocardiography","topic":"Ultrasound in Clinical Applications","field":"Medicine","cited_by":30,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; St. Michael's Hospital","funders":"","keywords":"Medicine; Confidence interval; Internal medicine; Critical illness; Retrospective cohort study; Severity of illness; Early warning score; Framingham Risk Score; Emergency department; Coronavirus disease 2019 (COVID-19); Critically ill; Emergency medicine; 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":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.0007752185,0.000193206,0.000393914,0.0001012436,0.0007943606,0.00009786721,0.0001953086,0.0001770386,0.00005989857],"category_scores_gemma":[0.00858138,0.0001460642,0.0008861834,0.001015106,0.0006042506,0.0000808601,0.00007460034,0.0004213337,0.000025768],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005829642,"about_ca_system_score_gemma":0.0002910979,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007431961,"about_ca_topic_score_gemma":0.00000558804,"domain_scores_codex":[0.9980078,0.0001162371,0.0004708212,0.0005557848,0.0003954137,0.000453915],"domain_scores_gemma":[0.9907646,0.007456002,0.00006641746,0.0008518241,0.0004743426,0.000386852],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001398249,0.0008538854,0.694858,0.0004313483,0.002974571,0.0001480998,0.0009840046,0.0002098595,0.002436401,0.1477016,0.1281451,0.01985891],"study_design_scores_gemma":[0.002799356,0.0004504791,0.125893,0.0001464333,0.001275945,0.0002704612,0.001477929,0.0002879763,0.001943233,0.1299383,0.7349542,0.0005627057],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.120707,0.004240726,0.8065473,0.04782392,0.001963978,0.003486854,0.000667647,0.0008398203,0.0137228],"genre_scores_gemma":[0.967882,0.0004023926,0.02381969,0.00499268,0.001017679,0.001305169,0.0001556679,0.00005538487,0.0003693063],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8471751,"threshold_uncertainty_score":0.9997697,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0433024297506134,"score_gpt":0.3613490711536245,"score_spread":0.3180466414030111,"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."}}