{"id":"W2085870631","doi":"10.1016/s0167-8655(03)00110-7","title":"QoS based video delivery with foveation and bandwidth monitoring","year":2003,"lang":"en","type":"article","venue":"Pattern Recognition Letters","topic":"Sparse and Compressive Sensing Techniques","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Computer science; Bandwidth (computing); Data compression; Real-time computing; Computer vision; Artificial intelligence; 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":[0.00004769002,0.0001236532,0.00009059477,0.00008854648,0.00005145115,0.00004830273,0.0000288347,0.00003661368,0.00002679348],"category_scores_gemma":[0.000005878347,0.0001216498,0.00002038002,0.00006545809,0.00002046252,0.0001331595,0.000003793399,0.00009274524,0.00001388575],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000279675,"about_ca_system_score_gemma":0.000003254296,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001347704,"about_ca_topic_score_gemma":0.000002671862,"domain_scores_codex":[0.9994867,0.00003007744,0.00009941129,0.0001423416,0.00009695398,0.0001444861],"domain_scores_gemma":[0.9997635,0.0000422781,0.00002400028,0.00009933327,0.00003044979,0.00004045985],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00005207717,0.00005904399,0.1362817,0.0001793031,0.0001807989,0.0001249864,0.0003745143,0.006367373,0.3528541,0.000003528905,0.004948587,0.498574],"study_design_scores_gemma":[0.001257948,0.00008960365,0.02467776,0.0006881377,0.00008306089,0.00005049621,0.00006734008,0.01350639,0.9572589,0.0001080226,0.001499452,0.0007128436],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8395593,0.00005036564,0.1593049,0.00009286695,0.0001641378,0.0001095206,0.000004006461,0.0003427558,0.0003721517],"genre_scores_gemma":[0.9945621,0.00002877515,0.004592641,0.0006520292,0.00009339735,0.00002614325,0.00001385633,0.00002939302,0.000001665225],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6044049,"threshold_uncertainty_score":0.4960734,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01559252504701109,"score_gpt":0.1881949734082888,"score_spread":0.1726024483612777,"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."}}