{"id":"W2113234775","doi":"10.1109/tmc.2010.173","title":"Flexible Broadcasting of Scalable Video Streams to Heterogeneous Mobile Devices","year":2010,"lang":"en","type":"article","venue":"IEEE Transactions on Mobile Computing","topic":"Multimedia Communication and Technology","field":"Social Sciences","cited_by":27,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Computer science; Scalability; Testbed; Broadcasting (networking); Mobile device; Computer network; Scalable Video Coding; Energy consumption; Channel (broadcasting); Efficient energy use; Bitstream; Real-time computing; Decoding methods; Telecommunications","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005805079,0.0004445043,0.0005285159,0.0002852396,0.0004256938,0.000577445,0.0006086279,0.0005175849,0.000514899],"category_scores_gemma":[0.002126598,0.0001806606,0.0002348484,0.0005633305,0.0005817703,0.001013071,0.0005820409,0.0005629492,0.0001111067],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004163359,"about_ca_system_score_gemma":0.0002111529,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001179969,"about_ca_topic_score_gemma":0.001008284,"domain_scores_codex":[0.999733,0.00008757293,0.0000112802,0.00004112156,0.00008107233,0.00004590023],"domain_scores_gemma":[0.9990381,0.000616838,0.00009078958,0.000116965,0.00009812033,0.00003924055],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0007810338,0.0001941215,0.001845466,0.0003084971,0.0001297115,0.0009713308,0.0005632465,0.6583416,0.1715267,0.03022925,0.001390929,0.133718],"study_design_scores_gemma":[0.00005797358,0.0002114344,0.0003763177,0.000008958413,0.00002421026,0.0001386101,0.0001032338,0.971894,0.02041972,0.005668742,0.001079591,0.00001717115],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.3005036,0.0007573073,0.6949865,0.0002743798,0.00006082632,0.0001031412,0.000052708,0.0002490217,0.003012553],"genre_scores_gemma":[0.9410774,0.0004134588,0.05758348,0.0000396608,0.00004985807,0.00004603087,0.00004549077,0.0000182481,0.0007263486],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.001179969,"threshold_uncertainty_score":0.003070056,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02226645719882147,"score_gpt":0.327763971506339,"score_spread":0.3054975143075175,"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."}}