{"id":"W2785996293","doi":"10.1109/hpcc-smartcity-dss.2017.20","title":"A Multi-core Multicast Approach for Delay and Delay Variation Multicast Routing","year":2017,"lang":"en","type":"article","venue":"","topic":"Network Traffic and Congestion Control","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Multicast; Computer science; Xcast; Protocol Independent Multicast; Computer network; Source-specific multicast; Distance Vector Multicast Routing Protocol; Distributed computing; Pragmatic General Multicast; Inter-domain; Routing (electronic design automation); End-to-end delay","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":[0.0005973536,0.0004058763,0.0004870732,0.0006296011,0.0007099403,0.0004658192,0.001205197,0.0005562847,0.0008648806],"category_scores_gemma":[0.000725835,0.0001724426,0.0004228405,0.0005405683,0.0002514595,0.0007842686,0.0008049127,0.0007498422,0.0001546803],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005981019,"about_ca_system_score_gemma":0.0006862705,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007167534,"about_ca_topic_score_gemma":0.001189111,"domain_scores_codex":[0.9995646,0.0001324846,0.00002189034,0.00007254288,0.0001557414,0.00005273924],"domain_scores_gemma":[0.9996902,0.00008577517,0.00003502268,0.00005483567,0.0001074347,0.0000267209],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002986966,0.0002434896,0.001047509,0.0004130289,0.0001500393,0.000321272,0.0003653936,0.3003499,0.08590482,0.1171917,0.005094064,0.48862],"study_design_scores_gemma":[0.00002607222,0.0002147123,0.0002296127,0.00002283844,0.00003199285,0.0002895198,0.00004869831,0.9573784,0.01207863,0.02153985,0.008122033,0.00001757585],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.009971749,0.0004015512,0.9876935,0.0001047624,0.00004926328,0.00005102663,0.00001598271,0.0001614471,0.001550713],"genre_scores_gemma":[0.411056,0.0004942436,0.5853026,0.0001999987,0.00006859691,0.0001489008,0.00008770959,0.00005059558,0.002591295],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001205197,"threshold_uncertainty_score":0.004339576,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04745818930391654,"score_gpt":0.2821028537992597,"score_spread":0.2346446644953432,"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."}}