{"id":"W2114003337","doi":"10.1023/b:nets.0000039784.00352.66","title":"A Strategic Model for Dynamic Traffic Assignment","year":2004,"lang":"en","type":"article","venue":"Networks and Spatial Economics","topic":"Transportation Planning and Optimization","field":"Social Sciences","cited_by":42,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université de Montréal","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Node (physics); Set (abstract data type); Computer science; Traffic flow (computer networking); Flow network; Mathematical optimization; Preference; Order (exchange); Star (game theory); Assignment problem; Operations research; Mathematics; Engineering; Computer network; Economics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0001337338,0.00005632861,0.0000803275,0.00001745158,0.0002424425,0.00006373831,0.00003765191,0.00008009529,0.00000544045],"category_scores_gemma":[0.000002197247,0.00006187125,0.00002754477,0.0000213312,0.00004415431,0.00007042951,0.000001700654,0.00004010154,5.450776e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000593696,"about_ca_system_score_gemma":0.000109394,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004046691,"about_ca_topic_score_gemma":0.01961045,"domain_scores_codex":[0.9995747,0.000007253412,0.0001230475,0.0001256398,0.00002566845,0.000143678],"domain_scores_gemma":[0.999817,0.00002177329,0.00005028899,0.00003219655,0.00001555642,0.00006322157],"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":[0.00001454893,0.00001152019,0.00004005566,0.000001665573,0.000004613583,1.077638e-7,0.001417302,0.9698094,1.458981e-7,0.02081668,0.000005101502,0.007878863],"study_design_scores_gemma":[0.0004181834,0.0000264836,0.0001741407,0.000005076916,0.000009794615,9.109851e-8,0.0002560108,0.9952103,1.382916e-7,0.00356464,0.000256355,0.00007878583],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2678979,0.00005261881,0.7305232,0.0004830336,0.0001482074,0.0001779084,0.00001373965,0.00003318693,0.0006701949],"genre_scores_gemma":[0.9971147,0.0004895055,0.002008381,0.000100224,0.00009262814,0.00001624223,0.00005535798,0.000007202271,0.0001157186],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7292168,"threshold_uncertainty_score":0.9982791,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02120370495492416,"score_gpt":0.2544721114554223,"score_spread":0.2332684065004981,"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."}}