{"id":"W4407948873","doi":"10.1109/jiot.2025.3546124","title":"Intelligent and Autonomous Edge Slicing for IoT Systems","year":2025,"lang":"en","type":"article","venue":"IEEE Internet of Things Journal","topic":"IoT and Edge/Fog Computing","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Computer science; Slicing; Internet of Things; Enhanced Data Rates for GSM Evolution; Edge computing; Distributed computing; Computer network; Computer security; Artificial intelligence; World Wide Web","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":[0.0004738543,0.0005856482,0.0004227389,0.0002115132,0.0004155827,0.0007305229,0.000801141,0.0003797815,0.001743538],"category_scores_gemma":[0.001006183,0.0002141731,0.0003253257,0.0002022603,0.0005519355,0.001174683,0.0009655816,0.000767144,0.0002543709],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008154604,"about_ca_system_score_gemma":0.0008940149,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005056888,"about_ca_topic_score_gemma":0.004614075,"domain_scores_codex":[0.9997899,0.00003802791,0.00001333153,0.00004668746,0.00006172781,0.00005026266],"domain_scores_gemma":[0.9996794,0.0001049568,0.00005037669,0.0000611768,0.00006875408,0.00003530412],"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":[0.0001412464,0.00006194931,0.001679278,0.00006950364,0.00001996102,0.0001368331,0.00006802925,0.8966666,0.01118642,0.008667969,0.001763749,0.0795384],"study_design_scores_gemma":[0.000003714939,0.00001541615,0.0001103916,0.000003790131,0.000003375137,0.00001029565,0.000008198052,0.9955323,0.001450172,0.002292569,0.0005666591,0.000003191733],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1357441,0.001011013,0.8459713,0.0005310515,0.0001329192,0.0001040847,0.0001413999,0.00364016,0.01272387],"genre_scores_gemma":[0.9639128,0.0001763583,0.03452052,0.0001112574,0.00001788502,0.00003075759,0.00008155148,0.00005221012,0.001096685],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005056888,"threshold_uncertainty_score":0.01005489,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01927380349719957,"score_gpt":0.2697694070002669,"score_spread":0.2504956035030673,"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."}}