{"id":"W4392943190","doi":"10.1109/icmla58977.2023.00201","title":"Detection of Coronavirus Disease (COVID-19) Based on Deep Features and Support Vector Machine<sup>*</sup>","year":2023,"lang":"en","type":"article","venue":"","topic":"COVID-19 diagnosis using AI","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Trois-Rivières","funders":"","keywords":"Coronavirus disease 2019 (COVID-19); Coronavirus; Support vector machine; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); 2019-20 coronavirus outbreak; Computer science; Virology; Artificial intelligence; Disease; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000286718,0.0002195983,0.0003089453,0.0003917417,0.0001112559,0.0000218676,0.00008283481,0.0001032072,0.0006344481],"category_scores_gemma":[0.001572334,0.0001862746,0.000125176,0.0004767276,0.0001059281,0.00005555436,0.00005536903,0.0001939036,0.00007828869],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002079162,"about_ca_system_score_gemma":0.0003590631,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007472759,"about_ca_topic_score_gemma":0.0001815328,"domain_scores_codex":[0.9984885,0.00007669933,0.000252744,0.0004536762,0.0004441723,0.000284177],"domain_scores_gemma":[0.9980158,0.0007494523,0.00007250161,0.0004669586,0.0000618503,0.000633473],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.02093955,0.00436501,0.5387303,0.009797873,0.0006511267,0.003975925,0.003524585,0.06730261,0.04990397,0.0009358486,0.09533767,0.2045356],"study_design_scores_gemma":[0.005925921,0.001462159,0.7337977,0.000214742,0.0004138048,0.00003183203,0.0001386883,0.1859381,0.01105616,0.0001561718,0.060387,0.0004777243],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9148452,0.0003704637,0.002882912,0.07709964,0.0003478562,0.001872015,0.0002674096,0.001602552,0.0007120083],"genre_scores_gemma":[0.964995,0.00003961048,0.0001246948,0.03367196,0.0001004317,0.00005453945,0.0001126468,0.00004488845,0.0008562541],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2040579,"threshold_uncertainty_score":0.7596059,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04982361864806317,"score_gpt":0.3543749961159426,"score_spread":0.3045513774678795,"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."}}