{"id":"W4380356141","doi":"10.1186/s12864-023-09410-5","title":"Integrative multi-omics approach for identifying molecular signatures and pathways and deriving and validating molecular scores for COVID-19 severity and status","year":2023,"lang":"en","type":"article","venue":"BMC Genomics","topic":"COVID-19 Clinical Research Studies","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"National Institute of General Medical Sciences; Natural Sciences and Engineering Research Council of Canada","keywords":"Omics; Disease; Proteomics; Metabolomics; Computational biology; Coronavirus disease 2019 (COVID-19); Biology; Genomics; Lipidomics; Bioinformatics; Medicine; Genetics; Genome; Infectious disease (medical specialty); Pathology; Gene","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":[0.00452814,0.001527877,0.001421693,0.006801151,0.0005924341,0.002420601,0.000785163,0.0006393894,0.001767519],"category_scores_gemma":[0.004526368,0.0002897398,0.002463032,0.003700674,0.0004410545,0.0008904282,0.0016581,0.00137036,0.0005370053],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008955085,"about_ca_system_score_gemma":0.001451166,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001760606,"about_ca_topic_score_gemma":0.002252311,"domain_scores_codex":[0.9984722,0.0005744604,0.0001596386,0.0003719741,0.0003068157,0.00011498],"domain_scores_gemma":[0.997424,0.001013329,0.0006149596,0.0003294547,0.0004243956,0.0001938658],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.002211484,0.001394282,0.4608999,0.001677676,0.006237902,0.0007662392,0.0005526762,0.06521589,0.1297157,0.006407544,0.004512492,0.3204082],"study_design_scores_gemma":[0.0001594358,0.001482655,0.3882206,0.0003130372,0.002392096,0.0009017338,0.0008542131,0.5241526,0.03699877,0.03582581,0.008459945,0.0002391252],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4109387,0.003710567,0.5649076,0.001178684,0.0001382629,0.0007232823,0.01355513,0.002144198,0.002703555],"genre_scores_gemma":[0.7289489,0.0008049785,0.2596728,0.0003405559,0.00007887139,0.0005479173,0.008959181,0.0001105106,0.0005363325],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006801151,"threshold_uncertainty_score":0.02394736,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1496941500564529,"score_gpt":0.4277696483625465,"score_spread":0.2780754983060936,"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."}}