{"id":"W2056880433","doi":"10.1145/1925101.1925102","title":"Optimal layered multicast","year":2011,"lang":"en","type":"article","venue":"ACM Transactions on Multimedia Computing Communications and Applications","topic":"Cooperative Communication and Network Coding","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Multicast; Computer science; Linear network coding; Computer network; Throughput; Distributed computing; Node (physics); Source-specific multicast; Application layer; Coding (social sciences); Xcast; Reliable multicast; Mathematics","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":["sts"],"consensus_categories":[],"category_scores_codex":[0.0003196329,0.0002347135,0.0002107972,0.0002233625,0.001518743,0.0001343232,0.00353261,0.00009131734,0.00004704934],"category_scores_gemma":[0.00003406407,0.0002447334,0.00009047078,0.0007758597,0.0003074957,0.0002950777,0.0003870767,0.0004972706,0.0001223309],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004353225,"about_ca_system_score_gemma":0.00005531342,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002385678,"about_ca_topic_score_gemma":0.00003080317,"domain_scores_codex":[0.9984312,0.0002054672,0.0004355738,0.0004687727,0.0001598736,0.0002990935],"domain_scores_gemma":[0.9940234,0.0007482892,0.0001404827,0.004666835,0.0002158674,0.0002050859],"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":[0.000004802058,0.0006299955,0.00008919266,0.00000604114,0.00005008957,4.657491e-7,0.00310647,0.0002694284,0.0004646871,0.02921284,0.00003991232,0.9661261],"study_design_scores_gemma":[0.001166058,0.0001679424,0.004020295,0.00008179526,0.00005121828,0.00004359256,0.0005246834,0.9448793,0.001672388,0.001816532,0.04479184,0.0007843488],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.001076691,0.0004708529,0.9929043,0.001713564,0.00006496468,0.0005689419,0.000009916614,0.0004785611,0.002712191],"genre_scores_gemma":[0.5390942,0.001313777,0.4590917,0.0002095345,0.0000181987,0.0001879546,0.000009392348,0.00001330086,0.00006194638],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9653417,"threshold_uncertainty_score":0.9997811,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07960425991603445,"score_gpt":0.3062453325447347,"score_spread":0.2266410726287003,"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."}}