{"id":"W68121058","doi":"","title":"Route Choice Modelling for Urban Commuters: Considering Bridge choice as a key determinant of selected routes","year":2013,"lang":"en","type":"article","venue":"Transportation Research Board 92nd 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":"TRIPS architecture; Bridge (graph theory); Transport engineering; Discrete choice; Travel behavior; Choice set; Mode choice; Population; Declaration; Value of time; Computer science; Set (abstract data type); Scale (ratio); Aggregate (composite); Operations research; Travel time; Geography; Econometrics; Public transport; Engineering; Economics; Demography","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":[0.00555031,0.0004821402,0.0007652061,0.001409264,0.002346191,0.0004423239,0.0009505448,0.000503743,0.0003444532],"category_scores_gemma":[0.001719388,0.0005334396,0.000315041,0.003200898,0.001394775,0.002048044,0.0000110615,0.001309634,0.00006508586],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000268491,"about_ca_system_score_gemma":0.001484212,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.1768157,"about_ca_topic_score_gemma":0.06149155,"domain_scores_codex":[0.9896438,0.001388013,0.001785883,0.001152944,0.003905329,0.002124099],"domain_scores_gemma":[0.9818982,0.005249939,0.0004839746,0.0005526363,0.01099997,0.0008152183],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001389339,0.001113621,0.6357877,0.001966635,0.0004802169,0.00006897032,0.2301357,0.07432237,0.00666349,0.02492258,0.01745962,0.005689756],"study_design_scores_gemma":[0.004793174,0.001235526,0.8670397,0.001319582,0.0001737083,6.26356e-7,0.03670062,0.01485249,0.003901718,0.002861373,0.06569131,0.001430148],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9745362,0.0002577337,0.01527689,0.002912193,0.000218854,0.004348996,0.0006913941,0.000398958,0.001358713],"genre_scores_gemma":[0.9808715,0.000393875,0.01422177,0.00008732917,0.0003214816,0.001233789,0.001239628,0.0001281397,0.001502519],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.231252,"threshold_uncertainty_score":0.9997117,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09456174737871358,"score_gpt":0.3950614714262899,"score_spread":0.3004997240475764,"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."}}