{"id":"W2141838214","doi":"10.1109/qshine.2005.17","title":"Delay Satisfaction End-to-End Priority Assignment and Routing in Multi- Class Priority Networks","year":2005,"lang":"en","type":"article","venue":"","topic":"Network Traffic and Congestion Control","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Computer science; Heuristic; Routing (electronic design automation); End-to-end principle; Quality of service; Computation; Distributed computing; End-to-end delay; Computer network; Mathematical optimization; Priority inheritance; Algorithm; Dynamic priority scheduling; Mathematics","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":[0.0007664107,0.0003399123,0.0003188122,0.000302537,0.0003421342,0.0009074425,0.0008628659,0.0003951267,0.0008477875],"category_scores_gemma":[0.002148196,0.0002178109,0.0001586271,0.0004211325,0.0003512264,0.00109883,0.0004163839,0.0005720505,0.0001980203],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007797939,"about_ca_system_score_gemma":0.0006781995,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00272208,"about_ca_topic_score_gemma":0.003181588,"domain_scores_codex":[0.9995018,0.0001509741,0.00001704488,0.00006393059,0.0001944752,0.00007178983],"domain_scores_gemma":[0.9993082,0.0003282122,0.00008569768,0.00006744332,0.0001626618,0.00004784044],"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":[0.0001561052,0.00008332345,0.001092657,0.00006878189,0.00001669953,0.00008168932,0.00009800353,0.7588555,0.01097702,0.04764413,0.001571004,0.179355],"study_design_scores_gemma":[0.000006989552,0.00001854015,0.0001224998,0.000001765989,0.000002752052,0.00002145735,0.00001132722,0.9911944,0.001841814,0.006012521,0.000762917,0.000003049592],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02345159,0.0002372364,0.9742054,0.0001183761,0.00002921077,0.00001906124,0.000010714,0.0001242973,0.00180419],"genre_scores_gemma":[0.7645426,0.0003825805,0.2307701,0.00006405988,0.00006845307,0.00004569665,0.00006368915,0.00006410218,0.003998695],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00272208,"threshold_uncertainty_score":0.005657792,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01465350829868846,"score_gpt":0.2483859066987742,"score_spread":0.2337323984000858,"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."}}