{"id":"W2241036302","doi":"10.2495/ut030221","title":"TRAVEL DEMAND FORECASTING AND TDM MEASURES: THE EXAMPLE OF MONTREAL'S SOUTH SHORE, 2001-2021","year":2003,"lang":"en","type":"article","venue":"WIT transactions on the built environment","topic":"Transportation Planning and Optimization","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Metropolitan area; Demand forecasting; Demand management; Shore; Transport engineering; Traffic congestion; Work (physics); Business; Regional science; Operations research; Geography; Economics; Engineering","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":[0.0005279741,0.000457159,0.0002290341,0.001126718,0.0008829331,0.001249247,0.001059544,0.0007002642,0.001719496],"category_scores_gemma":[0.002027448,0.0001830343,0.0003978541,0.00357661,0.0004390255,0.0005139222,0.0003502983,0.0006021968,0.00015686],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01476807,"about_ca_system_score_gemma":0.004528561,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9728347,"about_ca_topic_score_gemma":0.9794964,"domain_scores_codex":[0.9997289,0.00006215679,0.000008656935,0.00004590801,0.00007251897,0.00008193874],"domain_scores_gemma":[0.9992782,0.0002050765,0.00009306588,0.00004100497,0.0002833355,0.00009922394],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.0005117498,0.0003222188,0.4267676,0.0002317361,0.0003462274,0.002998217,0.00110866,0.4761008,0.001950411,0.008299061,0.02743309,0.05393025],"study_design_scores_gemma":[0.00007729537,0.0001672815,0.4919308,0.00005985474,0.0001064464,0.0001648981,0.004042615,0.4824504,0.00120338,0.0008814189,0.0187801,0.0001355516],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9697497,0.0005198867,0.001926772,0.002158818,0.00003139082,0.0001058907,0.009793381,0.0002022094,0.01551179],"genre_scores_gemma":[0.9926916,0.0002563858,0.001867892,0.00005789235,0.000009447018,0.00002407464,0.00240621,0.00001795211,0.00266854],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02716529,"threshold_uncertainty_score":0.1071503,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04973730286399573,"score_gpt":0.229862362510944,"score_spread":0.1801250596469483,"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."}}