{"id":"W563012626","doi":"","title":"Application of Dynamic Traffic Assignment (DTA) Model to Evaluate Network Traffic Impact During Bridge Closure - A Case Study in Edmonton, Alberta","year":2014,"lang":"en","type":"article","venue":"Transportation 2014: Past, Present, Future - 2014 Conference and Exhibition of the Transportation Association of Canada // Transport 2014 : Du passé vers l'avenir - 2014 Congrès et Exposition de 'Association des transports du Canada","topic":"Transportation Planning and Optimization","field":"Social Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Traffic flow (computer networking); Allowance (engineering); Transport engineering; Bridge (graph theory); Traffic generation model; Computer science; Queue; Traffic congestion reconstruction with Kerner's three-phase theory; Reliability (semiconductor); Traffic congestion; Calibration; Engineering; Operations research; Real-time computing; Computer network; Operations management; Statistics","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":[0.0009392532,0.0008792434,0.0004478526,0.001153257,0.001075668,0.001393619,0.001910761,0.001094971,0.0009919343],"category_scores_gemma":[0.001072182,0.0003506615,0.0006842783,0.001313529,0.0008086922,0.0005707826,0.0006845966,0.0007576394,0.00009766128],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01121124,"about_ca_system_score_gemma":0.006298936,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8463646,"about_ca_topic_score_gemma":0.8465134,"domain_scores_codex":[0.9995846,0.00006229201,0.00001607654,0.00007907273,0.0001336612,0.0001241884],"domain_scores_gemma":[0.9993951,0.0001973777,0.00005062837,0.00003852739,0.0002311862,0.00008711558],"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":[0.0001582894,0.0002559703,0.03599067,0.00004197841,0.00003275239,0.0009689957,0.0001644509,0.9498475,0.002222142,0.001105904,0.000749457,0.008461926],"study_design_scores_gemma":[0.00002446779,0.0001191011,0.01835111,0.00001004445,0.00002672581,0.00003923317,0.0005646701,0.9790227,0.0009250866,0.000249156,0.0006393399,0.00002840667],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9917192,0.00006639121,0.003327801,0.0001324544,0.00001597481,0.00006969881,0.0004708653,0.0001201281,0.004077317],"genre_scores_gemma":[0.9953318,0.00006230925,0.002322822,0.00001894067,0.00000294317,0.00002041268,0.0004571087,0.00001193864,0.001771779],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1536354,"threshold_uncertainty_score":0.3090804,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007678336015126368,"score_gpt":0.2457143189908506,"score_spread":0.2380359829757242,"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."}}