{"id":"W4386835558","doi":"10.18280/ria.370403","title":"SFoG-RPI: A Secured QoS Aware and Load Balancing Framework for FoG Computing in Healthcare Paradigm","year":2023,"lang":"en","type":"article","venue":"Revue d intelligence artificielle","topic":"Electronic Health Records Systems","field":"Health Professions","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Quality of service; Fog computing; Health care; Load balancing (electrical power); Distributed computing; Computer network; Internet of Things; Embedded system; Geology","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.003376437,0.0002873576,0.0006585642,0.0002649129,0.0009861677,0.00002725077,0.0003012049,0.0004821901,0.00005098504],"category_scores_gemma":[0.001278191,0.0002997965,0.00009479204,0.001210592,0.00006151635,0.0001058585,0.0001514015,0.001323448,0.0005619364],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007960885,"about_ca_system_score_gemma":0.0009004133,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00165163,"about_ca_topic_score_gemma":0.002213137,"domain_scores_codex":[0.9950939,0.0005873037,0.001491552,0.0007658199,0.0002726441,0.001788785],"domain_scores_gemma":[0.9945394,0.003971423,0.0003997102,0.0005657104,0.0002020947,0.0003216674],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0007066349,0.0003968114,0.3229421,0.03585667,0.0001376716,0.0001850932,0.1759004,0.01299901,0.001031626,0.269899,0.02730338,0.1526417],"study_design_scores_gemma":[0.0004974394,0.0005373709,0.003774815,0.009660401,0.00001951817,0.00002616338,0.02681227,0.8794373,0.0005089851,0.0391549,0.03871047,0.0008604195],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6462799,0.00619519,0.2843525,0.04189407,0.008556684,0.01059415,0.0001035879,0.001181682,0.0008421369],"genre_scores_gemma":[0.9946312,0.0005325567,0.001116225,0.001171869,0.0008923907,0.0004993838,0.00003153528,0.00007773816,0.001047084],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8664382,"threshold_uncertainty_score":0.9999454,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1075355197125278,"score_gpt":0.4411823366450997,"score_spread":0.3336468169325719,"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."}}