{"id":"W4387544181","doi":"10.1109/icdcs57875.2023.00095","title":"Digital Twin-Assisted Resource Demand Prediction for Multicast Short Video Streaming","year":2023,"lang":"en","type":"article","venue":"","topic":"Image and Video Quality Assessment","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Multicast; Computer science; Construct (python library); Computer network; Scheme (mathematics); Duration (music); Resource (disambiguation); On demand; Video on demand; Real-time computing; Distributed computing; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003771763,0.0001182472,0.0001308927,0.0001161687,0.0001802779,0.0004959155,0.0003563304,0.00005125184,0.0000051674],"category_scores_gemma":[0.0001043227,0.0001049104,0.00008686499,0.0003931568,0.00002556992,0.0008609153,0.000226765,0.00006570214,0.00005210531],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004561994,"about_ca_system_score_gemma":0.00003599504,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007070381,"about_ca_topic_score_gemma":0.000006648625,"domain_scores_codex":[0.9987149,0.00003058156,0.0002704556,0.0003895889,0.0002764794,0.0003179564],"domain_scores_gemma":[0.9991034,0.0003005144,0.0000334666,0.0003998189,0.00007054142,0.00009222609],"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":[0.00003392137,0.0002823747,0.006132459,0.0001157686,0.0001166411,0.00004586763,0.001475299,0.0004987164,0.00358862,0.01201966,0.04973077,0.9259599],"study_design_scores_gemma":[0.0009059116,0.0003028795,0.0522454,0.00006497622,0.00002456142,0.00002411903,0.0009520211,0.857368,0.00550271,0.0007876019,0.08142664,0.0003951866],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0219519,0.000008640689,0.9683015,0.0010541,0.0001780645,0.0003280993,0.00002673078,0.0007758394,0.007375123],"genre_scores_gemma":[0.9753988,0.000002214491,0.0177027,0.0002994243,0.000151785,0.00007358864,0.00007729376,0.00001500598,0.006279193],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9534469,"threshold_uncertainty_score":0.4782124,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04592948823981222,"score_gpt":0.3175161739599112,"score_spread":0.271586685720099,"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."}}