{"id":"W1999369615","doi":"10.1139/l02-064","title":"A simplified approach for the historical analysis of urban person travel","year":2002,"lang":"en","type":"article","venue":"Canadian Journal of Civil Engineering","topic":"Urban Transport and Accessibility","field":"Social Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada; University of Toronto","keywords":"Transport engineering; Travel behavior; Distribution (mathematics); Travel time; Work (physics); Trip generation; Population; Population growth; Econometrics; Geography; Statistics; Engineering; Mathematics; Demography; Sociology","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"about_ca":true,"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":[0.001716875,0.0008146088,0.0008237126,0.005666938,0.0007743115,0.002077678,0.00140475,0.0006025864,0.008055512],"category_scores_gemma":[0.00743553,0.0004417597,0.001287838,0.006405532,0.0006444535,0.002006327,0.001366664,0.001140319,0.001622242],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001807036,"about_ca_system_score_gemma":0.001499957,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02640984,"about_ca_topic_score_gemma":0.02059652,"domain_scores_codex":[0.9985026,0.0005348272,0.0001073184,0.000314403,0.0004546393,0.00008615348],"domain_scores_gemma":[0.9984848,0.0005766305,0.0001640071,0.0003085629,0.0004156783,0.00005040807],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001024849,0.0001944925,0.0280513,0.0007328349,0.0004397911,0.0006643311,0.002284643,0.1574544,0.004511346,0.4703952,0.01746343,0.3177058],"study_design_scores_gemma":[0.00003794004,0.0002901343,0.0645027,0.0003434395,0.0002583509,0.001842886,0.001559052,0.4431637,0.002055827,0.2279684,0.2576995,0.0002780502],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01266313,0.0008604234,0.9697978,0.0002703949,0.0001378232,0.0002628687,0.002853233,0.0003389827,0.01281527],"genre_scores_gemma":[0.2343568,0.003158534,0.741173,0.0002353861,0.0002976848,0.001606631,0.004621011,0.0002793846,0.01427164],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02640984,"threshold_uncertainty_score":0.05251223,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03873281957132337,"score_gpt":0.2244337843272325,"score_spread":0.1857009647559091,"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."}}