{"id":"W4399767788","doi":"10.1109/jiot.2024.3416054","title":"Knowledge-Collaboration-Based Resource Allocation in 6G IoT: A Graph Attention RL Approach","year":2024,"lang":"en","type":"article","venue":"IEEE Internet of Things Journal","topic":"IoT and Edge/Fog Computing","field":"Computer Science","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"Science and Technology Program of Suzhou; National Natural Science Foundation of China","keywords":"Computer science; Resource allocation; Graph; Resource management (computing); Distributed computing; Graph theory; Theoretical computer science; Computer network","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":[],"consensus_categories":[],"category_scores_codex":[0.001450761,0.0001527895,0.0001903415,0.0007200702,0.0000717927,0.0006532024,0.0007884229,0.00009707826,0.000002841372],"category_scores_gemma":[0.00006405083,0.0001403819,0.0001391516,0.001004329,0.00004170928,0.0006493358,0.00007626238,0.0005226581,0.00002390576],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001670798,"about_ca_system_score_gemma":0.0002160218,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003814129,"about_ca_topic_score_gemma":0.000003244008,"domain_scores_codex":[0.9983675,0.0001589803,0.0005689347,0.0003107904,0.0003410059,0.0002527771],"domain_scores_gemma":[0.9991512,0.0001256812,0.000211017,0.0002091992,0.0002249544,0.00007790067],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002531346,0.001988487,0.006596138,0.001993633,0.0005148129,0.0003574892,0.149902,0.02566146,0.06602044,0.01751778,0.2851311,0.4440636],"study_design_scores_gemma":[0.0003547551,0.0001089555,0.0004798048,0.0009088106,0.00001212835,0.0001122228,0.00009529639,0.9850973,0.004869129,0.001894963,0.005879288,0.0001873762],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1837009,0.0007606286,0.8036133,0.001059027,0.007837227,0.0001150598,1.014029e-7,0.0001080199,0.002805707],"genre_scores_gemma":[0.976037,0.000004643351,0.02220483,0.0001374215,0.001009868,0.000004864161,0.000002517531,0.00001645651,0.0005824308],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9594358,"threshold_uncertainty_score":0.6298846,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01635793419240597,"score_gpt":0.2658195325703261,"score_spread":0.2494615983779201,"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."}}