{"id":"W1562265786","doi":"10.1109/pacrim.2003.1235814","title":"A traffic engineered routing algorithm based on fuzzy logic","year":2004,"lang":"en","type":"article","venue":"","topic":"Formal Methods in Verification","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Static routing; Multipath routing; Link-state routing protocol; Routing (electronic design automation); Destination-Sequenced Distance Vector routing; Dijkstra's algorithm; Equal-cost multi-path routing; Distance-vector routing protocol; Policy-based routing; Fuzzy logic; Suurballe's algorithm; Dynamic Source Routing; Algorithm; Routing algorithm; Distributed computing; Routing protocol; Theoretical computer science; Computer network; Shortest path problem; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004537378,0.000108668,0.00009343039,0.0001025893,0.000070295,0.00007796461,0.0005224387,0.00005578182,0.000009915096],"category_scores_gemma":[0.000097469,0.00009297714,0.0000477383,0.000416453,0.00001692509,0.000226848,0.00003713856,0.0001165483,0.0001230636],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009381013,"about_ca_system_score_gemma":0.0000541123,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006329191,"about_ca_topic_score_gemma":4.56434e-7,"domain_scores_codex":[0.9990554,0.00004362431,0.0001658905,0.0002823628,0.000225066,0.0002276675],"domain_scores_gemma":[0.999318,0.00005032976,0.00004409936,0.0004877569,0.00003709997,0.00006273577],"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":[0.000002266261,0.00009412553,0.000001507025,0.000004787539,0.000002914034,0.000007440417,0.0001882871,0.2501188,0.0002672843,0.3955793,0.00002511872,0.3537081],"study_design_scores_gemma":[0.0003597572,0.0001305036,0.000258895,0.00001253779,0.000001428331,0.000005514602,0.00001083855,0.9909785,0.005346346,0.002594347,0.0001666045,0.0001346963],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001542433,0.000007365772,0.9897637,0.0005212439,0.0003123464,0.0001199819,5.422798e-7,0.0004972275,0.007235203],"genre_scores_gemma":[0.2851981,4.958105e-7,0.7141805,0.0005291355,0.00003240414,0.000008751826,0.000001089902,0.00000497413,0.00004452674],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.7408597,"threshold_uncertainty_score":0.3791498,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02701521044887948,"score_gpt":0.2728558046619393,"score_spread":0.2458405942130598,"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."}}