{"id":"W2015501914","doi":"10.1155/2009/682813","title":"A Cross‐Layer Framework for Efficient Streaming of H.264 Video over IEEE 802.11 Networks","year":2009,"lang":"en","type":"article","venue":"Journal of Computer Networks and Communications","topic":"Video Coding and Compression Technologies","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada; University of Calgary","keywords":"Computer science; Computer network; Video quality; Wireless network; Network packet; Transcoding; Transmission (telecommunications); Real-time computing; Layer (electronics); Heterogeneous network; Application layer; Wireless; Telecommunications","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":[0.001652992,0.0006672401,0.0003878915,0.0005533184,0.0003978469,0.000898143,0.001205951,0.0007372255,0.001085483],"category_scores_gemma":[0.001656757,0.0004008418,0.0005370165,0.0002626216,0.0004289792,0.0009664205,0.0008535892,0.00125631,0.0004265333],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004974754,"about_ca_system_score_gemma":0.001075787,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003029854,"about_ca_topic_score_gemma":0.003067047,"domain_scores_codex":[0.9994001,0.0001392382,0.00004791727,0.00006229215,0.0002921384,0.000058323],"domain_scores_gemma":[0.9996443,0.00009793159,0.00003310875,0.0000584148,0.0001360172,0.00003022981],"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":[0.0002756797,0.0002625967,0.001121938,0.0004371275,0.0002202633,0.001147465,0.0005283828,0.3843252,0.1227839,0.153661,0.01154418,0.3236923],"study_design_scores_gemma":[0.00002488732,0.0001527876,0.0002724638,0.00002876794,0.00004428436,0.0002147305,0.00002591216,0.9671302,0.0140212,0.006525274,0.01153068,0.00002873975],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.004620846,0.0003581135,0.9930139,0.00007982119,0.00004501376,0.00007622418,0.00002265095,0.0007723748,0.001011145],"genre_scores_gemma":[0.2165399,0.0009436694,0.7783217,0.000161939,0.0001520049,0.0003352675,0.0002560858,0.0001705294,0.003118848],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003029854,"threshold_uncertainty_score":0.008741915,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03033575589546076,"score_gpt":0.314397748184944,"score_spread":0.2840619922894832,"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."}}