{"id":"W7027514299","doi":"","title":"Comparison between MATSim &amp; EMME: Developing a Dynamic, Activity-based Microsimulation Transit Assignment Model for Toronto","year":2012,"lang":"en","type":"dissertation","venue":"TSpace (University of Toronto)","topic":"Transportation Planning and Optimization","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Public transport; Transit (satellite); Microsimulation; Schedule; Traffic congestion; Urban transit; Data collection; Rail transit","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":[0.0003203667,0.0006312856,0.0003209365,0.000319495,0.0003789911,0.0006852079,0.000841254,0.0004835554,0.003258303],"category_scores_gemma":[0.0009364497,0.0002678835,0.0005045079,0.0003558166,0.0002332986,0.0004233154,0.0004297819,0.0004464108,0.0004061362],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003254195,"about_ca_system_score_gemma":0.002633116,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.3055265,"about_ca_topic_score_gemma":0.2728786,"domain_scores_codex":[0.9998893,0.00002994831,0.00000651892,0.00002082729,0.00002962504,0.00002378099],"domain_scores_gemma":[0.9997098,0.0001102354,0.00002467875,0.00002818157,0.00009509339,0.00003206032],"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":[0.00003418217,0.00001541928,0.001150034,0.00001707783,0.000008312988,0.00001229519,0.00001609487,0.9944048,0.0003107736,0.0009778191,0.0002916113,0.00276167],"study_design_scores_gemma":[0.000006176682,0.00001471575,0.00041181,0.000002263083,0.000004682818,0.000001999642,0.00001357671,0.9985027,0.0002654633,0.00009392263,0.0006798156,0.000002971965],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8261421,0.0002423038,0.1198763,0.0006106627,0.0000838104,0.0002203673,0.003220473,0.001085309,0.0485187],"genre_scores_gemma":[0.9731196,0.0001720549,0.02051179,0.00003274634,0.000007661033,0.0001084927,0.001329892,0.00009435152,0.004623474],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6944735,"threshold_uncertainty_score":0.6074963,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05291134564165917,"score_gpt":0.3513647953858148,"score_spread":0.2984534497441557,"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."}}