{"id":"W3192229377","doi":"10.1109/icc42927.2021.9500460","title":"A Deep Learning-based System for Detecting COVID-19 Patients","year":2021,"lang":"en","type":"article","venue":"","topic":"COVID-19 diagnosis using AI","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"Alfaisal University","keywords":"Robustness (evolution); Coronavirus disease 2019 (COVID-19); Computer science; Artificial intelligence; Benchmark (surveying); Machine learning; Sensitivity (control systems); Deep learning; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Data mining; Pattern recognition (psychology); Engineering","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":[0.0006138919,0.0009492569,0.0006984969,0.001259479,0.0003697801,0.0006074153,0.001367088,0.001115958,0.003533188],"category_scores_gemma":[0.001315117,0.0003378818,0.0005483812,0.0004786594,0.0002136945,0.0006596876,0.0007828705,0.0008595031,0.00192439],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009983382,"about_ca_system_score_gemma":0.0008035815,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007844443,"about_ca_topic_score_gemma":0.009231137,"domain_scores_codex":[0.9995024,0.00004718037,0.00005221635,0.000209148,0.0001136434,0.0000754435],"domain_scores_gemma":[0.9996647,0.00007429747,0.00004271614,0.00003521923,0.0001454709,0.00003761875],"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":[0.001530791,0.001219521,0.04503691,0.0005606167,0.0002742246,0.001549634,0.0001915872,0.0353221,0.0570109,0.001188401,0.05422102,0.8018942],"study_design_scores_gemma":[0.000101256,0.0004893013,0.01438081,0.00007110091,0.0001091648,0.0008258543,0.00006226201,0.9241085,0.04920417,0.001244556,0.009328691,0.00007427912],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3253365,0.002637818,0.5572481,0.002708056,0.0009993785,0.001371416,0.01257001,0.08395904,0.01316977],"genre_scores_gemma":[0.7945639,0.0007134412,0.1804869,0.002003823,0.0001791342,0.0006587413,0.01104553,0.000208752,0.01013982],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007844443,"threshold_uncertainty_score":0.01559758,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03279687210305976,"score_gpt":0.3235012447640805,"score_spread":0.2907043726610207,"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."}}