{"id":"W1968911620","doi":"10.1109/cdc.2011.6161433","title":"A Markovian jump guaranteed cost congestion control strategy for mobile networks subject to differentiated services traffic","year":2011,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Markov process; Computer science; Network congestion; Quality of service; Network topology; Jump; Network traffic control; Control theory (sociology); Controller (irrigation); Computer network; Mathematical optimization; Topology (electrical circuits); Control (management); Engineering; Mathematics","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":[0.0006023277,0.0006434418,0.0005259512,0.0003422385,0.00031109,0.000606173,0.001193048,0.0005223423,0.0008356076],"category_scores_gemma":[0.0009914784,0.0001926378,0.0003258444,0.0003210458,0.0005697659,0.0006080345,0.0005681794,0.0007854896,0.00007434941],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001115676,"about_ca_system_score_gemma":0.001222892,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007261069,"about_ca_topic_score_gemma":0.004911729,"domain_scores_codex":[0.9995987,0.00007497021,0.00001660322,0.00007781007,0.0001561947,0.00007582869],"domain_scores_gemma":[0.9995981,0.0001444592,0.00007251971,0.00002346458,0.0001265204,0.00003483196],"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":[0.0001144385,0.00008486926,0.0004117652,0.0001083488,0.00004819434,0.0001315342,0.00008740586,0.8940521,0.01165581,0.03966085,0.001657163,0.05198753],"study_design_scores_gemma":[0.000009977366,0.00003247551,0.00005193345,0.000002031373,0.000005714927,0.000008685151,0.000002588192,0.9979476,0.0004656756,0.001237422,0.0002321931,0.000003713015],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02480473,0.0003434049,0.9726208,0.0001786826,0.0000911534,0.00004412626,0.00002374824,0.0001665478,0.001726867],"genre_scores_gemma":[0.9731827,0.0001950208,0.02496927,0.00007801246,0.00004887238,0.00006316484,0.00003089865,0.00001463572,0.001417444],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007261069,"threshold_uncertainty_score":0.01443762,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01297465275103598,"score_gpt":0.2170753254184364,"score_spread":0.2041006726674004,"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."}}