{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003007508,0.0006203401,0.0006022844,0.0006069509,0.000337171,0.0005404166,0.0006317872,0.0006148982,0.002377922],"category_scores_gemma":[0.0004940366,0.0001607088,0.0003807805,0.0002893647,0.0001434147,0.0005723258,0.0007528207,0.0002960237,0.0005205153],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002640165,"about_ca_system_score_gemma":0.0003000875,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007050856,"about_ca_topic_score_gemma":0.0009695838,"domain_scores_codex":[0.9995772,0.00007244106,0.00003585908,0.0001344878,0.0001454504,0.0000344708],"domain_scores_gemma":[0.9998252,0.00003576383,0.00003283818,0.0000189501,0.00006031795,0.00002698255],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.002769681,0.001376684,0.08012893,0.001365593,0.0004051231,0.003500429,0.0009675941,0.04091654,0.2582887,0.003068627,0.02232714,0.5848851],"study_design_scores_gemma":[0.000317262,0.003448552,0.07033768,0.0002225118,0.0003978394,0.004488576,0.0007909046,0.8161644,0.07924648,0.002642856,0.02172477,0.0002181298],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.5004811,0.003472286,0.4598625,0.00146539,0.001037121,0.0009350956,0.00147453,0.005934648,0.0253374],"genre_scores_gemma":[0.9480991,0.0006666044,0.04513882,0.0005211954,0.0001205159,0.0003047336,0.0005505233,0.00003451094,0.004564087],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.002377922,"threshold_uncertainty_score":0.007954955,"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."}}