{"id":"W610867851","doi":"","title":"Solving the Stochastic Multiclass Traffic Assignment Problem with Asymmetric Interactions and Vehicle Restrictions","year":2015,"lang":"en","type":"article","venue":"Transportation Research Board 94th Annual MeetingTransportation Research Board","topic":"Transportation Planning and Optimization","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Path (computing); Mathematical optimization; Computer science; Flow network; Sensitivity (control systems); Logit; Algorithm; Mathematics; Machine learning; Engineering","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","sts"],"consensus_categories":[],"category_scores_codex":[0.008466429,0.0003539135,0.0003728561,0.001457743,0.003728004,0.0005434508,0.0005456901,0.000243725,0.00007979414],"category_scores_gemma":[0.000841227,0.0002940285,0.0001091234,0.004979489,0.001739764,0.00133333,0.00001065979,0.00185631,0.00005806645],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004848912,"about_ca_system_score_gemma":0.001558003,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.025445,"about_ca_topic_score_gemma":0.1100402,"domain_scores_codex":[0.9897074,0.001986461,0.0009424507,0.0009507328,0.004857099,0.001555824],"domain_scores_gemma":[0.9909146,0.002677417,0.0002540743,0.0003853551,0.004673202,0.001095307],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.002994019,0.001366547,0.1282588,0.0003230222,0.000416461,0.0002277035,0.325458,0.4586979,0.0002798621,0.04221125,0.01691468,0.0228518],"study_design_scores_gemma":[0.005949331,0.001817562,0.5240527,0.0007163062,0.0002614734,0.000003069108,0.3805023,0.01652733,0.0001346303,0.001281383,0.06746472,0.001289221],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9551652,0.0004091367,0.02100695,0.01327228,0.0003204593,0.003776305,0.0002427624,0.0005758269,0.005231052],"genre_scores_gemma":[0.9922418,0.0002296763,0.003816144,0.00007603806,0.0002341045,0.0007261906,0.0002389154,0.00007625324,0.002360906],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4421705,"threshold_uncertainty_score":0.9999512,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08037243175632645,"score_gpt":0.3850123541440589,"score_spread":0.3046399223877325,"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."}}