{"id":"W2132812596","doi":"10.1109/dcc.2009.11","title":"Adaptive Rate Allocation Algorithm for Transmission of Multiple Embedded Bit Streams over Time-Varying Noisy Channels","year":2009,"lang":"en","type":"article","venue":"","topic":"Advanced Data Compression Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Algorithm; Transmission (telecommunications); Computer science; Channel (broadcasting); Image (mathematics); Network packet; Distortion (music); Binary number; Binary symmetric channel; Time complexity; Binary image; Decoding methods; Mathematical optimization; Image processing; Mathematics; Channel code; Computer vision; Bandwidth (computing); Telecommunications; Computer network","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":[0.000232896,0.0001804971,0.0002367865,0.0001356731,0.00009073451,0.00003968337,0.0006327878,0.00008387167,0.00003339253],"category_scores_gemma":[0.0000257172,0.0001509782,0.00008378761,0.0002791643,0.00002315479,0.001029064,0.00008619531,0.00007992155,0.000006364948],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003124874,"about_ca_system_score_gemma":0.00003726327,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001466416,"about_ca_topic_score_gemma":2.979959e-7,"domain_scores_codex":[0.9987007,0.00005797702,0.0003295832,0.0004491943,0.0002155376,0.0002469594],"domain_scores_gemma":[0.998848,0.0001967335,0.0001703263,0.0005234884,0.0001694288,0.00009207823],"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":[0.00002390959,0.0001035682,7.686809e-7,0.000004518705,0.000006551581,9.343495e-7,0.0001517048,0.000565558,0.123566,0.001252072,0.0008480953,0.8734763],"study_design_scores_gemma":[0.0003847905,0.000239875,0.00002098229,0.00004975188,0.000002993941,9.109382e-7,0.000004602729,0.5898035,0.4037682,0.005112971,0.000491908,0.0001194837],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0004338839,0.00004837112,0.998029,0.0001299444,0.00006040824,0.0006142156,0.0000219779,0.0004054246,0.000256756],"genre_scores_gemma":[0.09597031,0.00001499515,0.9032693,0.0002168816,0.00003503131,0.00003852782,0.00004013463,0.00001097508,0.0004038317],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.8733568,"threshold_uncertainty_score":0.6156713,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01819713975255483,"score_gpt":0.2800921718639965,"score_spread":0.2618950321114417,"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."}}