{"id":"W1987721478","doi":"10.1109/mmsp.2012.6343451","title":"Multi-scalable video multicast for heterogeneous playback requirements using a perceptual utility measure","year":2012,"lang":"en","type":"article","venue":"","topic":"Image and Video Quality Assessment","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"Multicast; Computer science; Scalability; Scalable Video Coding; Scheme (mathematics); Maximization; Video quality; Source-specific multicast; Computer network; Pragmatic General Multicast; Adaptation (eye); Distributed computing; Mathematical optimization","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":[],"consensus_categories":[],"category_scores_codex":[0.001107585,0.0002434355,0.0002699966,0.00006378814,0.0002970837,0.000208831,0.0006290802,0.0001034729,0.00009047471],"category_scores_gemma":[0.0001421264,0.0002154645,0.0001703421,0.0001714035,0.00006415696,0.001434164,0.000353634,0.0001124951,0.00008823368],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001430783,"about_ca_system_score_gemma":0.00008633958,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001754422,"about_ca_topic_score_gemma":0.00003606034,"domain_scores_codex":[0.9976029,0.0001678532,0.0004288938,0.0005004135,0.0004545677,0.0008454213],"domain_scores_gemma":[0.9985109,0.0001496401,0.000102329,0.0007628109,0.0001951565,0.0002791936],"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":[0.0007078146,0.02018735,0.2539422,0.001679572,0.001447174,0.00008253926,0.05580836,0.001577948,0.2545429,0.0185008,0.01235632,0.3791671],"study_design_scores_gemma":[0.002490858,0.0001708681,0.01446912,0.00004851263,0.00005729048,0.00004148859,0.0005354604,0.9534883,0.02326618,0.000116302,0.004567819,0.0007477747],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07040804,0.0001310591,0.9277834,0.0001306676,0.0004745786,0.0005616605,0.00001072674,0.000154964,0.0003449158],"genre_scores_gemma":[0.6406703,0.000001092965,0.3584825,0.0005260486,0.00009159087,0.00002642427,0.000003368241,0.00001216084,0.0001865965],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9519104,"threshold_uncertainty_score":0.8786386,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2241199457810876,"score_gpt":0.3898744295682736,"score_spread":0.165754483787186,"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."}}