{"id":"W2145996955","doi":"10.1109/iwcmc.2011.5982859","title":"Traffic-prediction-assisted dynamic bandwidth assignment for hybrid wireless optical networks","year":2011,"lang":"en","type":"article","venue":"","topic":"Advanced Photonic Communication Systems","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"","keywords":"Computer science; Quality of service; Computer network; Bandwidth (computing); Dynamic bandwidth allocation; Scalability; Throughput; Wireless network; Broadband; Bandwidth allocation; Broadband networks; Wireless broadband; Wireless; Distributed computing; Telecommunications","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":[0.0001467022,0.0001545904,0.0001901414,0.00004518995,0.00007551393,0.00001743449,0.0002586807,0.00006932904,0.000146859],"category_scores_gemma":[0.000007508324,0.0001528486,0.00008099683,0.00008975581,0.00003441976,0.00009568685,0.00003302636,0.0001452584,0.00001659451],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001619458,"about_ca_system_score_gemma":0.00001293074,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002642179,"about_ca_topic_score_gemma":0.00002454594,"domain_scores_codex":[0.9990786,0.00001936287,0.0003454609,0.0001718649,0.0001135372,0.0002712092],"domain_scores_gemma":[0.9991636,0.0001203481,0.00003378047,0.0005313422,0.00004132789,0.000109654],"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":[0.0001275042,0.0003271952,0.0002370069,0.0001616506,0.0004641438,0.000008461823,0.0008082265,0.7765204,0.00340402,0.00422134,0.006402832,0.2073172],"study_design_scores_gemma":[0.0005184594,0.0000428135,0.0008998467,0.00002594418,0.00002014955,0.00001901858,0.00009867104,0.992578,0.001374927,0.00005359748,0.00418545,0.0001830894],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03159958,0.0001912898,0.9535457,0.00001531308,0.0005804686,0.0004795466,0.0000203569,0.0008049311,0.01276274],"genre_scores_gemma":[0.9867792,0.00005890974,0.01241995,0.00001899518,0.00003539789,0.0002900517,0.0000465479,0.00005020795,0.0003007607],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9551796,"threshold_uncertainty_score":0.6232987,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02198423664800512,"score_gpt":0.2279772477523775,"score_spread":0.2059930111043724,"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."}}