{"id":"W2167717523","doi":"10.1109/wcnc.2008.379","title":"Heuristics for Jointly Optimizing FEC and ARQ for Video Streaming over IEEE802.11 WLAN","year":2008,"lang":"en","type":"article","venue":"","topic":"Wireless Networks and Protocols","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Computer science; Forward error correction; Automatic repeat request; Network packet; Heuristic; Heuristics; Algorithm; Channel (broadcasting); Retransmission; Hybrid automatic repeat request; Real-time computing; Computer network; Decoding methods; Telecommunications link","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":[0.0001971021,0.0001467272,0.0002038469,0.00004578967,0.000302304,0.0001493042,0.0002844274,0.00005874821,0.000006422913],"category_scores_gemma":[0.00003751129,0.0001258864,0.00007329205,0.00009761371,0.00003744438,0.0002587092,0.0001181511,0.00005938632,0.000001357691],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001815604,"about_ca_system_score_gemma":0.0000459719,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003850433,"about_ca_topic_score_gemma":0.00002908739,"domain_scores_codex":[0.9989502,0.00001611149,0.000219826,0.0003543712,0.0001172176,0.0003422456],"domain_scores_gemma":[0.9990721,0.0003792248,0.00008165701,0.0002881761,0.00007277606,0.0001061088],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003674031,0.0005954433,0.02664123,0.001234755,0.0002537368,0.0001387105,0.003993673,0.01343978,0.003067137,0.5408589,0.2079466,0.2014626],"study_design_scores_gemma":[0.001338373,0.0003000573,0.001409881,0.00006850143,0.000008752766,0.00004070336,0.00001601995,0.9507117,0.001128323,0.003770992,0.04086406,0.0003426397],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.007239949,0.00004698629,0.9880373,0.0002153399,0.0001558764,0.003755657,0.000007849124,0.0001093829,0.0004315974],"genre_scores_gemma":[0.2159919,0.00002092649,0.7790051,0.0009155868,0.0004322028,0.002644842,0.0000052733,0.00002812537,0.0009560534],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9372719,"threshold_uncertainty_score":0.5133497,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03462361858663745,"score_gpt":0.2713543420803322,"score_spread":0.2367307234936948,"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."}}