{"id":"W2122198105","doi":"10.1109/icc.2006.254726","title":"Traffic Engineering in BFWA Mesh Networks at Millimeter Wave Band","year":2006,"lang":"en","type":"article","venue":"2006 IEEE International Conference on Communications","topic":"Millimeter-Wave Propagation and Modeling","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Wireless mesh network; Scalability; Mesh networking; Computer network; Extremely high frequency; Distributed computing; Channel (broadcasting); Interference (communication); Channel allocation schemes; Radio spectrum; Control reconfiguration; Electronic engineering; Wireless; Wireless network; Telecommunications; Engineering","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":[0.0003682688,0.0002446274,0.0002112096,0.0005025721,0.0005430499,0.0007517149,0.0004746694,0.000576883,0.001037508],"category_scores_gemma":[0.002343204,0.0001860311,0.0001777567,0.0004297679,0.0003689792,0.0009020834,0.0004485204,0.0003677752,0.000126074],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008499232,"about_ca_system_score_gemma":0.0003446897,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002587171,"about_ca_topic_score_gemma":0.002095236,"domain_scores_codex":[0.9997544,0.00008941165,0.000009564403,0.00003562497,0.00005868643,0.00005245503],"domain_scores_gemma":[0.9993819,0.0003599516,0.00006636589,0.00004750199,0.0001069186,0.00003735065],"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":[0.0002117844,0.0000550685,0.002035371,0.00004238006,0.00001924928,0.0001823188,0.0001441515,0.850555,0.01556276,0.07023238,0.001616342,0.05934325],"study_design_scores_gemma":[0.000005601387,0.00001635605,0.0002127055,0.000002345875,0.000002441992,0.00003065669,0.00002645662,0.9832266,0.001080461,0.01457568,0.000817306,0.000003440875],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2163625,0.0002684259,0.7750871,0.0005486931,0.00006406453,0.00005938288,0.00008632565,0.0002306093,0.007292968],"genre_scores_gemma":[0.9453328,0.0002032234,0.05092384,0.00006124796,0.00004784886,0.00006921532,0.00009340465,0.00002655161,0.003241853],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002587171,"threshold_uncertainty_score":0.006166637,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06271020328224598,"score_gpt":0.2661835124456546,"score_spread":0.2034733091634086,"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."}}