{"id":"W4308884814","doi":"10.1093/biomethods/bpac029","title":"An ensemble prediction model for COVID-19 mortality risk","year":2022,"lang":"en","type":"article","venue":"Biology Methods and Protocols","topic":"COVID-19 diagnosis using AI","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; University of Calgary","funders":"Alberta Innovates","keywords":"Cohort; Receiver operating characteristic; Machine learning; Artificial intelligence; Key (lock); Medicine; Intensive care medicine; Preprocessor; Stage (stratigraphy); Cohort study; Computer science; Emergency medicine; Internal medicine","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":[0.002217065,0.001029813,0.00115959,0.001513208,0.0003849873,0.0008411686,0.0008202556,0.0007575502,0.001981516],"category_scores_gemma":[0.004630977,0.0002371082,0.0009214169,0.0006436491,0.000171666,0.0005785809,0.0005518884,0.001299879,0.0006226185],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006000592,"about_ca_system_score_gemma":0.0008246511,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008922888,"about_ca_topic_score_gemma":0.006205978,"domain_scores_codex":[0.9995049,0.0001592191,0.0000370969,0.0001352665,0.00008750286,0.00007605948],"domain_scores_gemma":[0.9979983,0.001167892,0.0001789274,0.0001303287,0.0004341374,0.00009044408],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0007162415,0.0004881145,0.1563472,0.00006156605,0.0004898167,0.0003749643,0.0001276798,0.6622881,0.002466089,0.001392559,0.007639059,0.1676087],"study_design_scores_gemma":[0.000007221426,0.00004345419,0.00525126,0.000008064924,0.00003340176,0.0000370816,0.000009247936,0.9935958,0.0002082482,0.000584589,0.0002123035,0.000009501588],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5978228,0.001357266,0.3903683,0.001396958,0.0003281417,0.0002442267,0.003676178,0.001392955,0.003413229],"genre_scores_gemma":[0.9591379,0.0003463404,0.03547627,0.0001340797,0.0001122283,0.000202269,0.002626238,0.00004208677,0.001922613],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008922888,"threshold_uncertainty_score":0.01774186,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2326581235830629,"score_gpt":0.5600133001034,"score_spread":0.3273551765203371,"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."}}