{"id":"W2093649999","doi":"10.1007/s11116-013-9510-5","title":"Learning-based framework for transit assignment modeling under information provision","year":2013,"lang":"en","type":"article","venue":"Transportation","topic":"Transportation Planning and Optimization","field":"Social Sciences","cited_by":23,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Transit (satellite); Computer science; Operations research; Process (computing); Service (business); Microsimulation; Focus (optics); Markov process; Public transport; Transport engineering; Engineering; Economics; 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":[0.003032117,0.001235626,0.003181346,0.001497907,0.0008255427,0.001984847,0.003667846,0.002571552,0.005634023],"category_scores_gemma":[0.006295997,0.001129667,0.001501518,0.002111142,0.001425302,0.0024898,0.002076936,0.002371523,0.0006973084],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002992775,"about_ca_system_score_gemma":0.003678542,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03611548,"about_ca_topic_score_gemma":0.02488782,"domain_scores_codex":[0.9986612,0.0006004774,0.00005699138,0.0002974598,0.0001871643,0.0001967288],"domain_scores_gemma":[0.9968933,0.002095122,0.000264368,0.0001103391,0.0004637622,0.0001730873],"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":[0.00002615748,0.00004329708,0.000233915,0.00003692646,0.0000291598,0.00002832868,0.00002203777,0.9781634,0.00006846083,0.01417239,0.0006690961,0.006506831],"study_design_scores_gemma":[0.000003024981,0.000004580231,0.00001901336,0.000002504139,0.000004025422,0.000002144902,0.000002419588,0.9958519,0.00001545007,0.004001842,0.00009115269,0.00000195533],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01045858,0.0003518198,0.9863104,0.0005026626,0.00004181305,0.00005914755,0.0002952254,0.0002103015,0.001770058],"genre_scores_gemma":[0.7694955,0.001142126,0.2133141,0.000357312,0.0003031135,0.0005856782,0.001125877,0.0001525348,0.0135237],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.03611548,"threshold_uncertainty_score":0.07181048,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02030669036379636,"score_gpt":0.2835261948582314,"score_spread":0.263219504494435,"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."}}