{"id":"W2577045917","doi":"10.1109/tvt.2017.2655011","title":"Delay-Aware Load Balancing Over Multipath Wireless Networks","year":2017,"lang":"en","type":"article","venue":"IEEE Transactions on Vehicular Technology","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Computer science; Computer network; End-to-end delay; Network packet; Transmission delay; Real-time computing; Traffic generation model; Processing delay; Network delay; Telecommunications link; Multipath propagation; Wireless network; Wireless; Channel (broadcasting); 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005486573,0.0007416275,0.0004910205,0.0007549673,0.000636193,0.0006454586,0.0006870519,0.0003619396,0.0006536698],"category_scores_gemma":[0.001629475,0.0002316895,0.0001852863,0.0008171363,0.0003739532,0.0008558636,0.0007513174,0.0003168514,0.000126105],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001079891,"about_ca_system_score_gemma":0.0007308226,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003427009,"about_ca_topic_score_gemma":0.004193993,"domain_scores_codex":[0.999716,0.00006483497,0.00001463361,0.00005095882,0.00007893251,0.00007461991],"domain_scores_gemma":[0.9993155,0.0003399545,0.0001305442,0.00005128888,0.0001134187,0.00004933119],"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":[0.00008562354,0.00002212409,0.0007081588,0.00003313123,0.00001878673,0.00004269954,0.00002435621,0.9577284,0.005866324,0.002108406,0.0003098967,0.03305206],"study_design_scores_gemma":[0.000007582349,0.00003152663,0.0001602312,0.000002392593,0.000006358884,0.00002148931,0.00001354583,0.9965419,0.001214028,0.001592752,0.0004029931,0.000005122588],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2333832,0.001345748,0.7607978,0.0002315307,0.00008981142,0.00006736374,0.00008554465,0.0008933889,0.003105621],"genre_scores_gemma":[0.9677385,0.0003229818,0.03098586,0.00002112271,0.0000249777,0.00002762078,0.00003429803,0.0000273222,0.0008172861],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003427009,"threshold_uncertainty_score":0.00783515,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005849736114490459,"score_gpt":0.2181252117010734,"score_spread":0.2122754755865829,"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."}}