{"id":"W4389880061","doi":"10.1109/jstsp.2023.3343626","title":"Digital Twin Based User-Centric Resource Management for Multicast Short Video Streaming","year":2023,"lang":"en","type":"article","venue":"IEEE Journal of Selected Topics in Signal Processing","topic":"Image and Video Quality Assessment","field":"Computer Science","cited_by":28,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University; University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China","keywords":"Multicast; Computer science; Computer network; Resource management (computing); Video streaming; Xcast; Source-specific multicast; Multimedia","routes":{"ca_aff":true,"ca_fund":true,"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":[0.00101597,0.0006918224,0.0008910639,0.000732466,0.0007196067,0.0008218192,0.001672202,0.0004889281,0.001257165],"category_scores_gemma":[0.002469355,0.0002361183,0.0003710526,0.0009614369,0.0005637965,0.002184175,0.001278955,0.0008113037,0.0002331623],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008912478,"about_ca_system_score_gemma":0.0008383376,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003505582,"about_ca_topic_score_gemma":0.003945619,"domain_scores_codex":[0.9992816,0.00021096,0.0000523807,0.0001773956,0.0001649927,0.0001126775],"domain_scores_gemma":[0.9990545,0.0003133396,0.0001216411,0.0001937576,0.0001990075,0.0001178522],"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":[0.0009126349,0.0003609221,0.004688494,0.0002074161,0.0001181503,0.0003363296,0.0004737375,0.3827636,0.05417794,0.02799123,0.005676314,0.5222932],"study_design_scores_gemma":[0.0000113018,0.0001058972,0.000341449,0.000003745152,0.000015585,0.00008984817,0.00005735894,0.9894494,0.004479888,0.004370541,0.001058296,0.00001666425],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1001472,0.0006386359,0.8961331,0.0001881155,0.00006778941,0.00008107816,0.000114426,0.0008277476,0.001801864],"genre_scores_gemma":[0.9306138,0.0002132185,0.06783229,0.0000691754,0.00004585083,0.00004768746,0.0001202662,0.00004944063,0.00100842],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003505582,"threshold_uncertainty_score":0.006970346,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03233416119960012,"score_gpt":0.311555165807342,"score_spread":0.2792210046077419,"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."}}