{"id":"W2162828436","doi":"10.1109/imtc.2008.4547105","title":"QoS-Aware Service Selection for Multimedia Transcoding","year":2008,"lang":"en","type":"article","venue":"","topic":"Caching and Content Delivery","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"Transcoding; Computer science; Quality of service; Selection (genetic algorithm); Multimedia; Service (business); Path (computing); Mobile QoS; Computer network; Routing (electronic design automation); Ant colony optimization algorithms; Selection algorithm; Distributed computing; Service provider; Artificial intelligence","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":[0.0004319345,0.0003586518,0.0004286344,0.0004773065,0.0004692392,0.0005863009,0.000502609,0.000433691,0.000790943],"category_scores_gemma":[0.001637388,0.0001296114,0.0002604458,0.0003902661,0.0002650665,0.0005750651,0.0003046118,0.0004899225,0.0003278721],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003458904,"about_ca_system_score_gemma":0.0003429835,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001216785,"about_ca_topic_score_gemma":0.001491509,"domain_scores_codex":[0.9995705,0.0001080015,0.00002443575,0.00005774205,0.0002059342,0.00003341812],"domain_scores_gemma":[0.9993694,0.000196947,0.00005659078,0.00007560163,0.0002526969,0.00004879156],"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":[0.0006188793,0.0002548232,0.004464193,0.0002223676,0.00008644083,0.0008870969,0.0003201972,0.0884292,0.3819423,0.01310292,0.003832306,0.5058392],"study_design_scores_gemma":[0.00003791875,0.0002526026,0.001865563,0.00001660278,0.00005016816,0.0009657291,0.00009379111,0.922572,0.06068346,0.005731449,0.007692998,0.00003772646],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1787792,0.001675196,0.8105576,0.0004061892,0.0001867575,0.0001625923,0.00004860148,0.001227892,0.006955967],"genre_scores_gemma":[0.8512071,0.0005344947,0.1453767,0.00009665217,0.00007274083,0.00004464063,0.00008960681,0.00008337296,0.002494638],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001216785,"threshold_uncertainty_score":0.002646029,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04697169146902461,"score_gpt":0.2373170735039761,"score_spread":0.1903453820349515,"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."}}