{"id":"W4413553575","doi":"10.1109/jiot.2025.3602389","title":"Joint Optimization of IRS and THz Resource Allocation in 6G IoT Networks: An Adaptive Online MADDPG Approach","year":2025,"lang":"en","type":"article","venue":"IEEE Internet of Things Journal","topic":"Advanced MIMO Systems Optimization","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"Natural Sciences and Engineering Research Council of Canada; National Science Foundation","keywords":"Computer science; Joint (building); Resource allocation; Internet of Things; Resource management (computing); Computer network; Telecommunications; Computer security; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000401102,0.000141184,0.0002846774,0.0003417608,0.00001911862,0.00002839777,0.000157669,0.0001159238,0.000004837742],"category_scores_gemma":[0.00005298906,0.0001433961,0.00004023472,0.0002369506,0.00004297996,0.0003677266,0.00002507754,0.0003317137,9.727862e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001476975,"about_ca_system_score_gemma":0.00002031767,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004378943,"about_ca_topic_score_gemma":0.00001036328,"domain_scores_codex":[0.9988484,0.00007335877,0.0006633951,0.0001437278,0.0001261419,0.0001449735],"domain_scores_gemma":[0.9993656,0.00003949284,0.0002759385,0.0001308381,0.0001399259,0.00004818609],"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":[0.00006205509,0.0000566831,0.000151904,0.00007505157,0.00004489573,0.000001235005,0.00144959,0.9946143,0.001231095,0.0001294132,0.0001630621,0.002020733],"study_design_scores_gemma":[0.0004730959,0.00009005224,0.0001837006,0.0006206297,0.00001973878,0.00003142198,0.0007334061,0.9955018,0.002120949,0.0001016494,0.00002095654,0.0001026114],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05800205,0.0005082412,0.9404016,0.00002861363,0.000214567,0.000160618,0.000001729452,0.00003656619,0.0006460653],"genre_scores_gemma":[0.8809273,0.0001176,0.1187255,0.00003073385,0.00006397968,0.000003777508,0.00001299231,0.00002421929,0.0000939127],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8229252,"threshold_uncertainty_score":0.5847523,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01374652870781791,"score_gpt":0.2298764514838917,"score_spread":0.2161299227760738,"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."}}