{"id":"W4289526446","doi":"10.1016/j.mcpro.2022.100277","title":"Early Prediction of COVID-19 Patient Survival by Targeted Plasma Multi-Omics and Machine Learning","year":2022,"lang":"en","type":"article","venue":"Molecular & Cellular Proteomics","topic":"Metabolomics and Mass Spectrometry Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":48,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba; University of Victoria; McGill University","funders":"Warren Y. Soper Charitable Trust; Fondation De Famille Alvin Segal; Jewish General Hospital; Ministry of Education and Science of the Russian Federation; Public Health Agency; Génome Québec; Genome British Columbia; National Cancer Institute; Ministère de l'Économie, de l’Innovation et des Exportations du Québec; Public Health Agency of Canada; McGill University; Ministry of Science and Higher Education of the Russian Federation; Fonds de recherche du Québec; Skolkovo Institute of Science and Technology; Genome Canada","keywords":"Coronavirus disease 2019 (COVID-19); Omics; Medicine; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Receiver operating characteristic; 2019-20 coronavirus outbreak; Computational biology; Internal medicine; Bioinformatics; Disease; Intensive care medicine; Biology; Virology; Infectious disease (medical specialty)","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0006477945,0.0006489361,0.0005981187,0.000671211,0.0001660535,0.0006460207,0.0002019173,0.0004077822,0.0004777197],"category_scores_gemma":[0.001199734,0.0001076848,0.000373251,0.0004357867,0.0001463364,0.0003056629,0.0004076771,0.0005815831,0.0002123983],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002335904,"about_ca_system_score_gemma":0.0002965785,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006670449,"about_ca_topic_score_gemma":0.001052495,"domain_scores_codex":[0.9997259,0.00009348393,0.00002573195,0.00007400536,0.00004071294,0.00004009069],"domain_scores_gemma":[0.9995093,0.000163572,0.000174202,0.00003748102,0.00005441808,0.00006090818],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001607894,0.0003141201,0.8314978,0.0001373847,0.0003242863,0.0004812544,0.0001313848,0.008463851,0.08621198,0.0003916915,0.001234796,0.06920359],"study_design_scores_gemma":[0.00005336736,0.001736324,0.7421163,0.00007401386,0.0002716306,0.001202256,0.0002776458,0.1980017,0.05120386,0.002509703,0.002479537,0.00007357205],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9712876,0.001381436,0.02442616,0.0003915308,0.00004510071,0.00004990327,0.001564498,0.0002641674,0.0005894317],"genre_scores_gemma":[0.9877375,0.0003626113,0.0105294,0.0001093134,0.00003255417,0.00002163723,0.001002875,0.00001085545,0.0001932371],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.000671211,"threshold_uncertainty_score":0.003425896,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01142509626776603,"score_gpt":0.2092569433646982,"score_spread":0.1978318470969322,"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."}}