{"id":"W4410809019","doi":"10.1109/access.2025.3574291","title":"Digital Twin-Assisted Load-Balanced User Association and AoI-Aware Scheduling in IoT Networks","year":2025,"lang":"en","type":"article","venue":"IEEE Access","topic":"Digital Transformation in Industry","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Laurentian University; York University; Toronto Metropolitan University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Internet of Things; Scheduling (production processes); Association (psychology); Computer network; Distributed computing; Embedded system; Engineering","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0009940687,0.0008625815,0.001018384,0.0005524063,0.0007229818,0.001011142,0.00158504,0.0006662161,0.001046799],"category_scores_gemma":[0.002171414,0.0003867616,0.0005313805,0.001223956,0.0006498568,0.001374144,0.001087007,0.0008125241,0.0002232311],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001070734,"about_ca_system_score_gemma":0.001482511,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003738133,"about_ca_topic_score_gemma":0.00396211,"domain_scores_codex":[0.9992132,0.000197193,0.00003636734,0.0001854042,0.0001902348,0.0001775792],"domain_scores_gemma":[0.9989803,0.0004120781,0.0001471055,0.00012021,0.00021727,0.0001230198],"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":[0.0001596244,0.00008072041,0.001154283,0.00008694336,0.00004769749,0.0001306623,0.0001055152,0.9141442,0.004295895,0.01280554,0.001323437,0.06566541],"study_design_scores_gemma":[0.000005305,0.00003073009,0.0001016524,0.000002691791,0.000007297938,0.00003424632,0.00001440978,0.99621,0.0004265979,0.00266272,0.0004987606,0.00000557576],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02538537,0.0006121162,0.9712849,0.0001356061,0.0001294376,0.00004385261,0.00004706592,0.0001927038,0.002169016],"genre_scores_gemma":[0.8629721,0.0005144949,0.1338435,0.0001617269,0.0001277598,0.00008179154,0.0001119941,0.00005703287,0.002129498],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003738133,"threshold_uncertainty_score":0.00776881,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01365508588004188,"score_gpt":0.2586349729976156,"score_spread":0.2449798871175737,"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."}}