{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002260177,0.0007477244,0.0006105743,0.002499706,0.0009857034,0.008668611,0.0006882236,0.002278575,0.1157662],"category_scores_gemma":[0.01175471,0.0002837007,0.0005888689,0.002583325,0.001031275,0.003229926,0.001453196,0.001082916,0.05298188],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001706621,"about_ca_system_score_gemma":0.001266695,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00304231,"about_ca_topic_score_gemma":0.002726061,"domain_scores_codex":[0.998373,0.0003832505,0.00009159068,0.0001684784,0.0008657328,0.0001178983],"domain_scores_gemma":[0.9932281,0.003625914,0.0004140337,0.001095083,0.001285718,0.0003510723],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001170692,0.00007187638,0.002254235,0.0003870662,0.00003485311,0.0003889614,0.0002809162,0.001761261,0.002262228,0.08099394,0.7639916,0.1474561],"study_design_scores_gemma":[0.00003302537,0.00006227065,0.004004008,0.00027905,0.00002299194,0.0008098198,0.0005177176,0.009079188,0.006163373,0.0465923,0.932386,0.00005029633],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.01505452,0.01067507,0.1893528,0.08334067,0.04797392,0.0008563841,0.03173482,0.02858865,0.5924232],"genre_scores_gemma":[0.1741541,0.02180324,0.1299671,0.00857262,0.03479813,0.000434034,0.04694732,0.008900201,0.5744233],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.1157662,"threshold_uncertainty_score":0.3872765,"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."}}