{"id":"W2147962236","doi":"10.1109/icns.2008.53","title":"Corouting: An IP Hybrid Routing Approach","year":2008,"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":"Polytechnique Montréal","funders":"","keywords":"Computer science; Jitter; Computer network; Scalability; Robustness (evolution); Network packet; Link-state routing protocol; Equal-cost multi-path routing; Open Shortest Path First; Shortest path problem; Distributed computing; Routing protocol; Routing (electronic design automation); Bandwidth (computing); Theoretical computer science; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001464342,0.000860979,0.0008094647,0.001084694,0.0008170935,0.001959689,0.003137167,0.001098554,0.004295026],"category_scores_gemma":[0.00143343,0.0003588844,0.0005080103,0.0009215341,0.0008104317,0.002830707,0.002291788,0.000911026,0.001258087],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006703301,"about_ca_system_score_gemma":0.0009966177,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001654575,"about_ca_topic_score_gemma":0.001732004,"domain_scores_codex":[0.9990581,0.0001997094,0.00005373147,0.000188555,0.0003699778,0.0001298935],"domain_scores_gemma":[0.9990645,0.0001870464,0.00005433134,0.0004087329,0.0002140928,0.00007130382],"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":[0.0003776443,0.0002731874,0.001087798,0.0005300213,0.0001649505,0.0004947706,0.000412635,0.07100083,0.03397861,0.1966546,0.01823617,0.6767889],"study_design_scores_gemma":[0.000147335,0.0003482691,0.0005775466,0.0001133047,0.0001547305,0.0009824553,0.0001739778,0.7042303,0.02974708,0.1081927,0.1552026,0.0001297102],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.009751976,0.0009031019,0.9657281,0.00040245,0.0004195011,0.0001706285,0.0001057586,0.005971868,0.01654657],"genre_scores_gemma":[0.2772126,0.001279101,0.6944481,0.0006962213,0.000275202,0.0003023679,0.000626384,0.0009898399,0.02417017],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004295026,"threshold_uncertainty_score":0.0143683,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02817118424176366,"score_gpt":0.2173301318950298,"score_spread":0.1891589476532661,"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."}}