{"id":"W3134032143","doi":"10.1109/mce.2021.3062800","title":"Consumer Electronic Devices: Evolution and Edge Security Solutions","year":2021,"lang":"en","type":"article","venue":"IEEE Consumer Electronics Magazine","topic":"IoT and Edge/Fog Computing","field":"Computer Science","cited_by":24,"is_retracted":false,"has_abstract":true,"ca_institutions":"École de Technologie Supérieure","funders":"","keywords":"Computer science; Computer security; Mobile device; Enhanced Data Rates for GSM Evolution; Authentication (law); The Internet; Edge device; Variety (cybernetics); Telecommunications; World Wide Web; Cloud computing","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0005968281,0.0003682571,0.0003924402,0.0001812057,0.0005721102,0.0003028267,0.000583539,0.0001823952,0.0000143103],"category_scores_gemma":[0.0000958025,0.0004067653,0.000129313,0.0009946311,0.0001573547,0.0005786103,0.0003652305,0.0007679618,0.0003042995],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004351618,"about_ca_system_score_gemma":0.001613753,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002290006,"about_ca_topic_score_gemma":0.0002845472,"domain_scores_codex":[0.9964111,0.0002215326,0.0004557116,0.0009164055,0.0003439461,0.001651297],"domain_scores_gemma":[0.9981321,0.000224754,0.0001653077,0.0008261626,0.0004265183,0.0002251295],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000100173,0.001452914,0.01637344,0.0005275671,0.001440968,0.0003637706,0.002210038,0.0001138956,0.07968115,0.5482616,0.202741,0.1467335],"study_design_scores_gemma":[0.002116759,0.0002516259,0.003884307,0.0001064127,0.000202089,0.001125005,0.00002068244,0.08084549,0.007469172,0.05405769,0.8484636,0.001457183],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2809268,0.1776278,0.5177454,0.004469203,0.0102382,0.0007484056,0.00000636299,0.001300728,0.006937065],"genre_scores_gemma":[0.9939223,0.001762902,0.002153177,0.0006992953,0.0006239469,0.00002806236,0.00002399578,0.00004085066,0.0007454613],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7129955,"threshold_uncertainty_score":0.9998384,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01299618006425829,"score_gpt":0.2352643775070757,"score_spread":0.2222681974428174,"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."}}