{"id":"W4312553195","doi":"10.2139/ssrn.4243428","title":"Prediction of Severe COVID-19 Infection at the Time of Testing: A Machine Learning Approach","year":2022,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"COVID-19 diagnosis using AI","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"IBM (Canada); University of Toronto","funders":"","keywords":"Coronavirus disease 2019 (COVID-19); Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); 2019-20 coronavirus outbreak; Virology; Computer science; Medicine; Artificial intelligence; Internal medicine; Outbreak; 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":[0.001874325,0.0009400598,0.001244807,0.003278898,0.0004235447,0.001577062,0.001206189,0.001375833,0.00215955],"category_scores_gemma":[0.007287615,0.0002511274,0.0009860529,0.001052585,0.0002982023,0.0008908979,0.0005713497,0.001669868,0.001053624],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003977843,"about_ca_system_score_gemma":0.0006714262,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004292233,"about_ca_topic_score_gemma":0.003432648,"domain_scores_codex":[0.9991657,0.0002357956,0.0001122441,0.0002102972,0.0001414675,0.0001345694],"domain_scores_gemma":[0.9950824,0.003348736,0.0005109035,0.0001450014,0.0005872819,0.000325683],"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":[0.001640993,0.001397029,0.7672585,0.0001620447,0.0003601349,0.0006502716,0.0001152269,0.04670024,0.003751041,0.0009007951,0.005983323,0.1710804],"study_design_scores_gemma":[0.00005709688,0.0005802599,0.0848877,0.00006096653,0.0001721539,0.0005791321,0.0001859024,0.9072154,0.001563089,0.003804075,0.0008578556,0.00003639738],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.836537,0.002398282,0.1447372,0.003129546,0.000398524,0.0002886433,0.004400859,0.001084881,0.007025169],"genre_scores_gemma":[0.9796833,0.0002873721,0.01665013,0.0002006047,0.0002115629,0.00004818802,0.001930176,0.00001709717,0.000971511],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004292233,"threshold_uncertainty_score":0.009912491,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02892075065759106,"score_gpt":0.2774016621922987,"score_spread":0.2484809115347077,"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."}}