{"id":"W4295924696","doi":"10.1155/2022/9879259","title":"Remote Monitoring of COVID-19 Patients Using Multisensor Body Area Network Innovative System","year":2022,"lang":"en","type":"article","venue":"Computational Intelligence and Neuroscience","topic":"Wireless Body Area Networks","field":"Engineering","cited_by":31,"is_retracted":false,"has_abstract":true,"ca_institutions":"Professional Engineers Ontario","funders":"Universiti Tenaga Nasional; Tenaga Nasional Berhad","keywords":"Coronavirus disease 2019 (COVID-19); Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); 2019-20 coronavirus outbreak; Computer science; Remote sensing; Real-time computing; Artificial intelligence; Medicine; Virology; Geography; Internal medicine; Outbreak","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":[0.0001876843,0.0001333632,0.0001591157,0.0001194544,0.0004110805,0.00003081835,0.0002367804,0.00002378328,0.000004567818],"category_scores_gemma":[0.00009049283,0.0001511106,0.00002356453,0.00112681,0.0001456691,0.000142289,0.0001753469,0.0001892863,6.474713e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001665248,"about_ca_system_score_gemma":0.0000548687,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000169876,"about_ca_topic_score_gemma":2.640933e-7,"domain_scores_codex":[0.9987017,0.00006250071,0.000331595,0.0002774096,0.0003874895,0.0002393028],"domain_scores_gemma":[0.9993,0.0002411281,0.0001095461,0.0001133849,0.0001308488,0.0001050987],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00000908439,0.00001364303,0.01267532,0.00006011497,0.000003076077,0.000009829031,0.0002169151,0.9847751,0.0004670387,0.0003569041,0.00004136819,0.001371625],"study_design_scores_gemma":[0.00006635822,0.00005354909,0.008097663,0.00003956986,0.000003615005,0.00002338806,0.0002068925,0.9902722,0.0006943438,0.0003231408,0.00008417555,0.0001351114],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5354478,0.0001325753,0.4631462,0.000008672115,0.0009409729,0.0001583128,0.00002085387,0.0000928401,0.00005177444],"genre_scores_gemma":[0.9963287,0.00001900464,0.003492252,0.00006803497,0.00005798264,0.000005926519,0.000006469236,0.00001579911,0.000005791511],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.460881,"threshold_uncertainty_score":0.6162111,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06365300947227158,"score_gpt":0.2940595120374086,"score_spread":0.230406502565137,"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."}}