{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003439027,0.001035431,0.0008003055,0.001697785,0.0002431139,0.0008720563,0.0006623467,0.0004616798,0.0009140896],"category_scores_gemma":[0.0101747,0.0002496763,0.0005703897,0.0007023136,0.0002975125,0.000877554,0.0009830152,0.0009275944,0.000288708],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004551881,"about_ca_system_score_gemma":0.0008917222,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001593804,"about_ca_topic_score_gemma":0.002357647,"domain_scores_codex":[0.9985475,0.0005912629,0.000128538,0.0002254063,0.0004020739,0.0001051713],"domain_scores_gemma":[0.995582,0.00140077,0.001569869,0.0002116384,0.0007173592,0.0005184284],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0005847535,0.00007070904,0.9873568,0.00002446927,0.0001227845,0.00003883824,0.00001577252,0.001106957,0.0003785917,0.00002560604,0.0004176475,0.009857079],"study_design_scores_gemma":[0.0001806921,0.001678904,0.9523939,0.00006534885,0.0001631217,0.000591306,0.00007908569,0.04304475,0.0009297608,0.0001566121,0.0006864688,0.00002987646],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9909602,0.0009135387,0.004980444,0.0003144511,0.00005601237,0.0001193649,0.001455615,0.0001020546,0.001098422],"genre_scores_gemma":[0.9942316,0.0001489452,0.003748186,0.00006135659,0.00006814724,0.00005470304,0.001555346,0.000007896188,0.0001238911],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003439027,"threshold_uncertainty_score":0.01818752,"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."}}