{"id":"W4246001271","doi":"10.1002/wcm.701","title":"Channel assignment for multicast in multi‐channel multi‐radio wireless mesh networks","year":2008,"lang":"en","type":"article","venue":"Wireless Communications and Mobile Computing","topic":"Mobile Ad Hoc Networks","field":"Computer Science","cited_by":49,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"","keywords":"Multicast; Computer science; Computer network; Source-specific multicast; Unicast; Throughput; Xcast; Protocol Independent Multicast; Wireless mesh network; Pragmatic General Multicast; Channel (broadcasting); Distributed computing; Distance Vector Multicast Routing Protocol; Node (physics); Network packet; Wireless network; Wireless; 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":[0.0008214442,0.0002317372,0.0003541393,0.0005895124,0.0006303531,0.0004341152,0.0005780353,0.0003489541,0.001668035],"category_scores_gemma":[0.002099387,0.0001384819,0.0001827043,0.0004348153,0.0003531633,0.0007626372,0.0007993536,0.0004006199,0.000211493],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004605789,"about_ca_system_score_gemma":0.0003287854,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006336642,"about_ca_topic_score_gemma":0.0007869877,"domain_scores_codex":[0.9995969,0.0001972979,0.00001518046,0.00003790197,0.00007519864,0.00007756632],"domain_scores_gemma":[0.9991506,0.0005088674,0.00009051933,0.00008015914,0.0001233396,0.00004638689],"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":[0.0004679402,0.0001548171,0.002884357,0.000300806,0.00007105256,0.0002306753,0.0002303895,0.5650469,0.01968491,0.05853781,0.006355816,0.3460345],"study_design_scores_gemma":[0.00002584921,0.00006225452,0.0002295929,0.00001283854,0.00001310238,0.00006832185,0.00003766619,0.9780217,0.002669987,0.01638525,0.002465479,0.000007970007],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06560402,0.0009280528,0.9293314,0.0003147253,0.0001140375,0.00006860455,0.00004740914,0.000345354,0.003246306],"genre_scores_gemma":[0.862314,0.0003443384,0.1356843,0.00007477794,0.00007674904,0.000108833,0.00007484285,0.00003647014,0.001285689],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001668035,"threshold_uncertainty_score":0.005580127,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05223035414448596,"score_gpt":0.2897389234527742,"score_spread":0.2375085693082882,"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."}}