{"id":"W2022961962","doi":"10.1109/icc.2006.254859","title":"Slope Domain Modeling and Analysis of Data Communication Networks: A Network Calculus Complement","year":2006,"lang":"en","type":"article","venue":"2006 IEEE International Conference on Communications","topic":"Network Traffic and Congestion Control","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Complement (music); Network calculus; Computer science; Frequency domain; Legendre transformation; Algorithm; Domain (mathematical analysis); Domain analysis; Network analysis; Dual (grammatical number); Calculus (dental); Theoretical computer science; Applied mathematics; Mathematics; Mathematical analysis; Telecommunications","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":[0.0007755191,0.0001804755,0.0003181999,0.0002386916,0.0003235411,0.0002170161,0.005222762,0.00006985653,0.00005769719],"category_scores_gemma":[0.00001468715,0.0001862172,0.00008155024,0.0007106797,0.000172009,0.00047994,0.00118043,0.0002587309,0.000008892908],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005770876,"about_ca_system_score_gemma":0.00008077236,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000597304,"about_ca_topic_score_gemma":0.002835865,"domain_scores_codex":[0.9980028,0.0003093908,0.0006674626,0.0004130622,0.0003696044,0.0002376366],"domain_scores_gemma":[0.9951446,0.0003760105,0.0003284645,0.003638464,0.0004454568,0.00006697937],"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":[0.00001084019,0.000129499,0.0005105869,0.000001189618,0.0002937412,4.281972e-7,0.00006525724,0.3007935,0.00001079553,0.6769958,0.00141555,0.01977281],"study_design_scores_gemma":[0.0003475624,0.00002130695,0.0007353229,0.00004986146,0.0001237614,0.000001785574,0.00005139435,0.9883736,7.515083e-7,0.006859623,0.003266083,0.0001689671],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.001991965,0.0007627773,0.9763266,0.006798163,0.0001511067,0.0002282003,0.0001243868,0.00009821595,0.01351862],"genre_scores_gemma":[0.9197085,0.000890035,0.07783989,0.0002813025,0.00007135144,0.00004576706,0.001040506,0.000008540494,0.0001141312],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9177165,"threshold_uncertainty_score":0.9705278,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1065234614758738,"score_gpt":0.3396266418671379,"score_spread":0.233103180391264,"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."}}