{"id":"W1967265256","doi":"10.1109/music.2012.34","title":"Data Overhead Impact of Multipath Routing for Multicast in Wireless Mesh Networks","year":2012,"lang":"en","type":"article","venue":"","topic":"Mobile Ad Hoc Networks","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"","keywords":"Computer network; Computer science; Multicast; Xcast; Protocol Independent Multicast; Multipath routing; Source-specific multicast; Distance Vector Multicast Routing Protocol; Distributed computing; Dynamic Source Routing; Routing protocol; Routing (electronic design automation)","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":[0.001123739,0.0001771198,0.0003066682,0.00006475676,0.00004488777,0.0000538548,0.001608555,0.0001072233,0.00001785188],"category_scores_gemma":[0.00009102934,0.0001447738,0.00009032126,0.0003624644,0.00003547766,0.001205758,0.001002324,0.0001676024,0.00000436585],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007811448,"about_ca_system_score_gemma":0.00005513997,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003693338,"about_ca_topic_score_gemma":0.0001727445,"domain_scores_codex":[0.9981697,0.00007073484,0.0004288812,0.0004114509,0.0001784047,0.0007408924],"domain_scores_gemma":[0.9975238,0.0005590018,0.0001599319,0.001541089,0.0000561098,0.0001600106],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001102053,0.001286745,0.4765535,0.00007011795,0.0001659509,0.000007943628,0.001943126,0.0349324,0.0009086851,0.1287519,0.007889105,0.3473803],"study_design_scores_gemma":[0.0006381076,0.000053537,0.0356112,0.00003932781,0.000005131872,0.00000429494,0.00001934269,0.9633061,0.00007993692,0.00002804306,0.00005005024,0.0001649537],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09149217,0.00007265258,0.9071671,0.00002357795,0.0003070489,0.0004722486,0.00002038067,0.00006948732,0.0003753263],"genre_scores_gemma":[0.9483598,0.00001035304,0.05126378,0.00004720731,0.00021558,0.00002430588,0.00002869086,0.00001631808,0.00003398675],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9283737,"threshold_uncertainty_score":0.5903702,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0530648101102676,"score_gpt":0.3297565287439104,"score_spread":0.2766917186336428,"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."}}