{"id":"W4205371761","doi":"10.2196/preprints.19103","title":"The Use of Digital Health in the Detection and Management of COVID-19 (Preprint)","year":2020,"lang":"en","type":"preprint","venue":"","topic":"COVID-19 diagnosis using AI","field":"Medicine","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"Memorial University of Newfoundland","funders":"","keywords":"Preprint; Coronavirus disease 2019 (COVID-19); Triage; Outbreak; Digital health; Health care; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Telemedicine; 2019-20 coronavirus outbreak; Computer science; Infectious disease (medical specialty); Computer security; Data science; Internet privacy; Medical emergency; Business; Medicine; Virology; Disease; World Wide Web; Pathology; Political science","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":[0.0006873661,0.0001560131,0.0003720584,0.0001001014,0.00005408671,0.00006852936,0.0002017596,0.00008126316,0.000009886085],"category_scores_gemma":[0.0006417446,0.00009319714,0.0001003917,0.000199338,0.0001389748,0.00003845283,0.0007238124,0.000363071,0.000002007519],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002466607,"about_ca_system_score_gemma":0.0003053066,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002221961,"about_ca_topic_score_gemma":0.0005196768,"domain_scores_codex":[0.9984848,0.0001304431,0.0005284966,0.0003852514,0.0003221144,0.000148817],"domain_scores_gemma":[0.9978274,0.0009753983,0.0002965275,0.0007452947,0.00004541821,0.0001100391],"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":[0.00327349,0.002671638,0.06516586,0.06609906,0.002183967,0.0002450381,0.02721326,0.01456956,0.0004099485,0.01155242,0.06769806,0.7389177],"study_design_scores_gemma":[0.004469214,0.001136673,0.2100832,0.003159159,0.0004333091,0.00005361893,0.005215621,0.009597301,0.000813827,0.008423623,0.7560783,0.0005361639],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.1296472,0.001059152,0.02494151,0.8366156,0.0003235257,0.006675947,0.0000744351,0.0001417201,0.0005209695],"genre_scores_gemma":[0.975046,0.003711801,0.0005644839,0.02044251,0.00002957946,0.00009427164,0.00001427681,0.00001746531,0.00007963177],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8453988,"threshold_uncertainty_score":0.3800469,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1101206929939328,"score_gpt":0.3686262180473766,"score_spread":0.2585055250534438,"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."}}