{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003739443,0.0006908361,0.0003714051,0.00099194,0.0001457832,0.0005570477,0.0006007316,0.0005463699,0.00136483],"category_scores_gemma":[0.000901251,0.0001614596,0.0005079853,0.0005409571,0.0001229609,0.0004874369,0.0004876196,0.0004265712,0.0009203381],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004045742,"about_ca_system_score_gemma":0.0003624572,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005097481,"about_ca_topic_score_gemma":0.008243506,"domain_scores_codex":[0.9998109,0.00002473752,0.00001584923,0.00004596802,0.00005134368,0.00005127977],"domain_scores_gemma":[0.9997399,0.00007389652,0.00003786909,0.00002937856,0.00009090875,0.00002795401],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0005208774,0.0003461781,0.06668335,0.0002185878,0.0002374539,0.0006639673,0.00008152793,0.02322592,0.04379529,0.000749802,0.01390422,0.8495727],"study_design_scores_gemma":[0.00002917903,0.0006708195,0.07211533,0.0001055539,0.000155709,0.001432347,0.0002120065,0.8640535,0.04853466,0.002430949,0.01021091,0.0000490438],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6860927,0.003799388,0.2833853,0.0009478011,0.0005295677,0.0003824326,0.006861306,0.005639022,0.01236248],"genre_scores_gemma":[0.8954324,0.0007775745,0.09158496,0.0002133572,0.00009511631,0.00008136754,0.006736265,0.00005694923,0.005021928],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005097481,"threshold_uncertainty_score":0.01013559,"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."}}