{"id":"W4387870345","doi":"10.1109/icc45041.2023.10279382","title":"Digital Twin-Assisted Collaborative Transcoding for Better User Satisfaction in Live Streaming","year":2023,"lang":"en","type":"article","venue":"","topic":"Image and Video Quality Assessment","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University; University of Toronto; University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Transcoding; Computer science; User satisfaction; Multimedia; Video streaming; Human–computer interaction; Computer network","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":[0.0007685444,0.0007483014,0.0007610621,0.0003478717,0.0003976329,0.0006641729,0.001240589,0.0006236575,0.001739567],"category_scores_gemma":[0.002977014,0.0001977927,0.0003834285,0.0004463217,0.0003936274,0.001622932,0.0009167158,0.0009809822,0.0002679417],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004858954,"about_ca_system_score_gemma":0.0004947334,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002427232,"about_ca_topic_score_gemma":0.002877229,"domain_scores_codex":[0.9994708,0.0001149819,0.00003307469,0.0001389679,0.0001661733,0.00007592535],"domain_scores_gemma":[0.9987722,0.0004163114,0.0000948988,0.000186991,0.0004159785,0.0001135356],"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":[0.0009034324,0.000498339,0.005676459,0.0002189466,0.0001205368,0.0006160195,0.0003747061,0.4026035,0.09639685,0.0147269,0.003627588,0.4742366],"study_design_scores_gemma":[0.000008866699,0.00007279709,0.0003385981,0.00000304687,0.00001119169,0.00009861579,0.00002305754,0.9931101,0.004099658,0.001899557,0.0003246719,0.000009901644],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06428038,0.0002631391,0.9330647,0.0001471262,0.00005755388,0.00005246181,0.00005454832,0.0004602359,0.001619918],"genre_scores_gemma":[0.9261411,0.0001628408,0.07195695,0.0001012525,0.00005168243,0.00003832278,0.00006787576,0.00004828076,0.001431777],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002427232,"threshold_uncertainty_score":0.00581944,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.036505595755729,"score_gpt":0.3205696885541127,"score_spread":0.2840640927983837,"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."}}