{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002721337,0.0001833785,0.000317219,0.0001482135,0.0001950874,0.00004479956,0.00007467692,0.0001644827,0.0001988988],"category_scores_gemma":[0.001133379,0.0001835363,0.0001036109,0.0007451202,0.0001926245,0.00004910908,0.00006267574,0.0001603386,0.00003587114],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000382259,"about_ca_system_score_gemma":0.00108165,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00420484,"about_ca_topic_score_gemma":0.0005508962,"domain_scores_codex":[0.9983112,0.0001368229,0.0003286617,0.0006424829,0.0003469295,0.0002339046],"domain_scores_gemma":[0.9979255,0.0005355097,0.0001522573,0.0006488808,0.0001521615,0.0005856651],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001316198,0.001209602,0.9476544,0.0003317868,0.0003836204,0.00006138081,0.0004966599,0.0000391202,0.01943704,0.00003333104,0.02415005,0.00607142],"study_design_scores_gemma":[0.003979271,0.0001420581,0.7734132,0.0001144761,0.001003117,0.00001143978,0.000105362,0.007244104,0.01254661,0.0003231879,0.2008588,0.0002583904],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9495059,0.0007685805,0.01533994,0.0319863,0.0003340944,0.0008596538,0.0007288267,0.0004469385,0.00002980182],"genre_scores_gemma":[0.980666,0.000154715,0.001850586,0.01527411,0.0004091651,0.0005786353,0.000982478,0.00003216531,0.00005218724],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1767088,"threshold_uncertainty_score":0.7484393,"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."}}