{"id":"W4306657270","doi":"10.18280/ijsse.120405","title":"A Multi-Layered Edge-Secured Cloud Framework for Healthcare Monitoring in Old-Age Homes Using Smart Systems Driven by Comprehensive User Interaction","year":2022,"lang":"en","type":"article","venue":"International Journal of Safety and Security Engineering","topic":"IoT and Edge/Fog Computing","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Cloud computing; Computer science; Latency (audio); Edge computing; Enhanced Data Rates for GSM Evolution; Computer security; Process (computing); Architecture; Computer network; Telecommunications; Operating system","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003802661,0.0001466988,0.0002749106,0.0002959671,0.0001414344,0.0001513625,0.0004774252,0.00006218196,4.945921e-7],"category_scores_gemma":[0.00007543796,0.0001647149,0.00009524285,0.0001734053,0.000009695851,0.0005277154,0.0002776029,0.0005902281,1.673328e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004385266,"about_ca_system_score_gemma":0.00003957412,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008178948,"about_ca_topic_score_gemma":9.299771e-7,"domain_scores_codex":[0.9986001,0.00007148341,0.0005436327,0.0001752578,0.0003614366,0.0002480871],"domain_scores_gemma":[0.9989882,0.0003101067,0.0002924016,0.00009350106,0.0002192446,0.00009653006],"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":[0.0008466729,0.0005978892,0.03511554,0.0006693458,0.0008537123,0.0004465776,0.04633779,0.8792927,0.01581913,0.01343348,0.0005223528,0.006064799],"study_design_scores_gemma":[0.00117078,0.0001092178,0.002406842,0.0006651307,0.000008163707,0.0003565768,0.001106445,0.9840949,0.0003212843,0.0002144119,0.009292228,0.0002540087],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4071711,0.00163424,0.5633066,0.0004112304,0.02729649,0.0001451937,0.000007456934,0.00002664942,0.000001080168],"genre_scores_gemma":[0.9675319,0.0001124679,0.03049821,0.00004273221,0.001785265,0.000005491489,0.000005450317,0.00001479247,0.000003659816],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5603608,"threshold_uncertainty_score":0.6716878,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02717036776963586,"score_gpt":0.2936490604624487,"score_spread":0.2664786926928128,"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."}}