{"id":"W3215293155","doi":"10.3390/biomed1020011","title":"COVID-19 Prognosis and Mortality Risk Predictions from Symptoms: A Cloud-Based Smartphone Application","year":2021,"lang":"en","type":"article","venue":"BioMed","topic":"COVID-19 diagnosis using AI","field":"Medicine","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Pandemic; Intensive care unit; Cloud computing; Coronavirus disease 2019 (COVID-19); Medicine; Computer science; Intensive care medicine; Emergency medicine; Artificial intelligence; Machine learning; Medical emergency; Internal medicine; Disease; Infectious disease (medical specialty)","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":[0.0003539967,0.0009187086,0.0006495193,0.0005652558,0.0001980503,0.000469305,0.0005480225,0.0005600356,0.002187565],"category_scores_gemma":[0.001417003,0.0001596409,0.0002961564,0.000286783,0.00008645504,0.0004454978,0.0005129382,0.0003715292,0.0007132408],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002421599,"about_ca_system_score_gemma":0.0003118654,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003600899,"about_ca_topic_score_gemma":0.003330891,"domain_scores_codex":[0.9997897,0.00003780079,0.00003062404,0.00005009616,0.00005989884,0.00003193386],"domain_scores_gemma":[0.999469,0.0002154577,0.00005640282,0.00004556128,0.0001397398,0.0000739058],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.006175471,0.003050871,0.158249,0.00139685,0.0005775104,0.005638154,0.000824654,0.05241881,0.06416839,0.001647372,0.08937811,0.6164749],"study_design_scores_gemma":[0.0003955197,0.0009373635,0.06538597,0.0001404432,0.0002012817,0.001237729,0.0003282149,0.9031698,0.01532558,0.00108094,0.01166405,0.0001330066],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8363727,0.003090183,0.09419796,0.002897814,0.00071141,0.0009501795,0.01011191,0.04305442,0.008613421],"genre_scores_gemma":[0.9592279,0.0006649146,0.03346748,0.0004953805,0.0001212756,0.0001512591,0.003628794,0.0001365875,0.002106471],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003600899,"threshold_uncertainty_score":0.007318199,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02974996133494585,"score_gpt":0.3261335959737354,"score_spread":0.2963836346387896,"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."}}