{"id":"W3094100206","doi":"10.3390/electronics9111753","title":"Real-Time Remote Health Monitoring System Driven by 5G MEC-IoT","year":2020,"lang":"en","type":"article","venue":"Electronics","topic":"Telecommunications and Broadcasting Technologies","field":"Engineering","cited_by":73,"is_retracted":false,"has_abstract":true,"ca_institutions":"École de Technologie Supérieure; Université du Québec à Montréal","funders":"","keywords":"Cloud computing; Telemedicine; Computer science; Edge computing; Internet of Things; Big data; Low latency (capital markets); Enhanced Data Rates for GSM Evolution; Health care; Real-time computing; Computer network; Telecommunications; Computer security; Data mining; Operating system","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":[0.00009838321,0.0001452721,0.0002145103,0.00003759878,0.0001262804,0.0000337995,0.0004285067,0.00009127348,0.000004509876],"category_scores_gemma":[0.00002832624,0.0001566662,0.00004139297,0.0002887829,0.00001584115,0.00004095817,0.0000578036,0.0003859228,0.00007396767],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004131435,"about_ca_system_score_gemma":0.00005188006,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002086217,"about_ca_topic_score_gemma":0.000003117313,"domain_scores_codex":[0.999037,0.0000276879,0.0002332587,0.0001623999,0.000107458,0.0004322442],"domain_scores_gemma":[0.9993969,0.00003644659,0.00005338197,0.0004123336,0.00002114449,0.00007981287],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002093099,0.00005024874,0.0004073606,0.0008173847,0.0003066701,0.00001035836,0.001367334,0.02436257,0.4182121,0.002963691,0.08532152,0.4661598],"study_design_scores_gemma":[0.0006455258,0.0006268537,0.0002071559,0.0003261968,0.00003633452,0.00003444768,0.000573459,0.6498141,0.09645172,0.0001773338,0.2502079,0.0008990012],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8495367,0.07595216,0.01914859,0.01198164,0.0005050232,0.001069046,0.00006781126,0.03056295,0.0111761],"genre_scores_gemma":[0.9730134,0.005619114,0.02109621,0.00002136378,0.0000946914,0.000007593109,0.00001793952,0.00006226539,0.00006742124],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6254515,"threshold_uncertainty_score":0.6388661,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01338251606914824,"score_gpt":0.2323399845372449,"score_spread":0.2189574684680966,"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."}}