{"id":"W4311219348","doi":"10.1088/1742-6596/2386/1/012033","title":"How Machine Learning Applied in Covid-19 Prevention &amp; Control","year":2022,"lang":"en","type":"article","venue":"Journal of Physics Conference Series","topic":"COVID-19 diagnosis using AI","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"The Scarborough Hospital; University of Toronto","funders":"","keywords":"Coronavirus disease 2019 (COVID-19); Pandemic; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Hygiene; Control (management); Transmission (telecommunications); 2019-20 coronavirus outbreak; Artificial intelligence; Computer science; Outbreak; Machine learning; Risk analysis (engineering); Medicine; Virology; Infectious disease (medical specialty); Disease; Telecommunications","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":[0.0006583828,0.0001551432,0.0004931854,0.0001814842,0.0001805872,0.00009771905,0.0001628031,0.00003748101,0.0002736771],"category_scores_gemma":[0.0004991569,0.0001493483,0.000144345,0.0003176212,0.00008006363,0.0003188814,0.00007851684,0.0008608189,0.000002886954],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004090348,"about_ca_system_score_gemma":0.001118383,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004298247,"about_ca_topic_score_gemma":0.0000794762,"domain_scores_codex":[0.9985055,0.0002011593,0.0003719746,0.0001698881,0.0005450025,0.000206428],"domain_scores_gemma":[0.99872,0.0002165115,0.0005608479,0.0001650609,0.0001733506,0.0001642534],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.01551794,0.00527351,0.1110428,0.002039419,0.001284855,0.001015828,0.02759605,0.08629268,0.325299,0.05989232,0.01318991,0.3515557],"study_design_scores_gemma":[0.03053007,0.005379985,0.01183957,0.0007643171,0.0008604747,0.0009415772,0.009970667,0.00218091,0.02257882,0.05393837,0.859902,0.001113267],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5671453,0.001219232,0.1963256,0.2321015,0.0009428126,0.00151539,0.00005568681,0.0001660573,0.0005283682],"genre_scores_gemma":[0.994744,0.00009469718,0.0005634993,0.003678824,0.0002000712,0.00002831238,0.00002256109,0.00002114347,0.0006468611],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8467121,"threshold_uncertainty_score":0.6090246,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0472569850696789,"score_gpt":0.3186981724432194,"score_spread":0.2714411873735405,"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."}}