{"id":"W4252013762","doi":"10.1177/0361198106196400122","title":"Noniterative Approach to Dynamic Traffic Origin–Destination Estimation with Parallel Evolutionary Algorithms","year":2006,"lang":"en","type":"article","venue":"Transportation Research Record Journal of the Transportation Research Board","topic":"Transportation Planning and Optimization","field":"Social Sciences","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Dynode; Estimator; Computer science; Computation; Block (permutation group theory); Algorithm; Mathematical optimization; Multiprocessing; Parallel computing; Mathematics; Statistics","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":[0.001035421,0.0007006757,0.000807873,0.0006723076,0.0004474526,0.0007954161,0.001345185,0.0007141253,0.001356325],"category_scores_gemma":[0.003722618,0.0005409144,0.0004656461,0.000731326,0.000652107,0.0008854454,0.0009145191,0.0008602291,0.0001798355],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007097935,"about_ca_system_score_gemma":0.001242154,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006186487,"about_ca_topic_score_gemma":0.005364812,"domain_scores_codex":[0.9995993,0.0001488739,0.00001558564,0.00006826901,0.0001254742,0.00004251015],"domain_scores_gemma":[0.9989035,0.0007187105,0.0001035256,0.0000873776,0.0001602373,0.00002660851],"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":[0.00001285984,0.0000155504,0.0002256678,0.00001274292,0.00001206107,0.00002135963,0.00002009718,0.9764575,0.0003557278,0.006062604,0.0001114741,0.01669229],"study_design_scores_gemma":[0.000002360935,0.000002776001,0.00001857224,7.513041e-7,0.000001133874,0.000003041082,0.000001534314,0.9985138,0.00009513728,0.001263519,0.00009651767,9.517003e-7],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.008625895,0.00004070512,0.9900221,0.00006647017,0.00001072653,0.00001602646,0.000008714789,0.0001112866,0.001098018],"genre_scores_gemma":[0.4804008,0.0001385639,0.5148713,0.00009372652,0.00004753649,0.0002026272,0.0000644168,0.00009766049,0.004083308],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006186487,"threshold_uncertainty_score":0.01230097,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05645975005882906,"score_gpt":0.3821162116220462,"score_spread":0.3256564615632171,"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."}}