{"id":"W2030738966","doi":"10.3141/2279-03","title":"Path-Based Algorithms to Solve C-Logit Stochastic User Equilibrium Assignment Problem","year":2012,"lang":"en","type":"article","venue":"Transportation Research Record Journal of the Transportation Research Board","topic":"Transportation Planning and Optimization","field":"Social Sciences","cited_by":40,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Multinomial logistic regression; Logit; Computer science; Mathematical optimization; Path (computing); Line search; Line (geometry); Algorithm; Flow (mathematics); Flow network; Mathematics; Machine learning","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001714387,0.0009829005,0.00120212,0.001226665,0.0007344336,0.000779137,0.001691318,0.001276939,0.006959253],"category_scores_gemma":[0.005076088,0.0005936349,0.0007430253,0.001451533,0.0007781427,0.001439253,0.001390906,0.001819785,0.001058573],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00101906,"about_ca_system_score_gemma":0.002957153,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01232792,"about_ca_topic_score_gemma":0.01052058,"domain_scores_codex":[0.9993021,0.0003449846,0.00002919527,0.0000951298,0.0001466825,0.00008192353],"domain_scores_gemma":[0.9979689,0.001431076,0.000110173,0.00007883694,0.0003433445,0.00006771198],"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":[0.00004721953,0.00007672999,0.0005653608,0.00006364277,0.00003158512,0.00003378598,0.00006162742,0.9018916,0.0003005949,0.02174115,0.001735747,0.073451],"study_design_scores_gemma":[0.00001262428,0.00001348982,0.00003972351,0.000003690544,0.000002577826,0.00001006471,0.000009201963,0.9938946,0.00008884886,0.005453129,0.0004678458,0.00000416716],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.003974555,0.00007832303,0.9940888,0.00008373173,0.00001806333,0.00007348147,0.00002474992,0.0002516233,0.001406698],"genre_scores_gemma":[0.1635408,0.0002350112,0.8314534,0.0001159642,0.00003151107,0.0005524801,0.0002095355,0.0001617615,0.003699581],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01232792,"threshold_uncertainty_score":0.02451229,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1075548394023005,"score_gpt":0.4051072927315346,"score_spread":0.2975524533292341,"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."}}