{"id":"W2462943687","doi":"10.1109/vtcspring.2016.7504509","title":"Traffic Assignment with Maximum Delay Constraint in Stochastic Network","year":2016,"lang":"en","type":"article","venue":"","topic":"Transportation Planning and Optimization","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Computer science; Bottleneck; Constraint (computer-aided design); Mathematical optimization; Network delay; Flow network; Routing (electronic design automation); Path (computing); Set (abstract data type); Assignment problem; Maximum flow problem; Computer network; 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":[0.001097132,0.0007739962,0.001015692,0.0007804646,0.0009420629,0.001154788,0.001104496,0.0009516553,0.001669199],"category_scores_gemma":[0.003010237,0.0005828636,0.0007036207,0.001582444,0.0009482634,0.00188862,0.001015634,0.0007622561,0.000140003],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00232627,"about_ca_system_score_gemma":0.00173692,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008907653,"about_ca_topic_score_gemma":0.00613459,"domain_scores_codex":[0.9988894,0.0003631652,0.00003813643,0.0002731602,0.000168571,0.0002675655],"domain_scores_gemma":[0.9986676,0.0007630067,0.0002242634,0.00006700651,0.0001540997,0.0001240139],"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":[0.00005031228,0.00002021072,0.0003703876,0.00005417471,0.00001589599,0.00007058353,0.0000301681,0.9661881,0.0009379984,0.02720902,0.000628866,0.004424286],"study_design_scores_gemma":[0.000007397218,0.00001566695,0.0001146838,0.00000380574,0.000006184634,0.00002514533,0.00001438868,0.9789296,0.0002166215,0.0201973,0.0004632298,0.000006047587],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07812884,0.0003525942,0.917284,0.0003940353,0.00005433146,0.00006415568,0.0003030845,0.0001607147,0.003258224],"genre_scores_gemma":[0.9373871,0.0005670537,0.05922938,0.00008532962,0.00006083125,0.0001486572,0.0002831217,0.00003776702,0.002200792],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008907653,"threshold_uncertainty_score":0.01771158,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01340400970775242,"score_gpt":0.2482515637961521,"score_spread":0.2348475540883997,"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."}}