{"id":"W2154889564","doi":"10.3141/2498-01","title":"Heuristic Approach to Capacitated Traffic Assignment Problem for Large-Scale Transport Networks","year":2015,"lang":"en","type":"article","venue":"Transportation Research Record Journal of the Transportation Research Board","topic":"Transportation Planning and Optimization","field":"Social Sciences","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Göteborgs Universitet; Chalmers Tekniska Högskola","keywords":"Mathematical optimization; Heuristic; Benchmark (surveying); Computer science; Convergence (economics); Reliability (semiconductor); Flow network; Scale (ratio); Traffic flow (computer networking); Sensitivity (control systems); Operations research; Mathematics; Engineering; Economics","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","sts"],"consensus_categories":[],"category_scores_codex":[0.01342629,0.0003389193,0.0006194288,0.001082309,0.00158283,0.0002002116,0.001225652,0.0003661865,0.00007121649],"category_scores_gemma":[0.0003121562,0.0002838366,0.0004671342,0.003549999,0.0005613145,0.0007368496,0.000003433737,0.00166918,0.00001356065],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005589791,"about_ca_system_score_gemma":0.001834007,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005367453,"about_ca_topic_score_gemma":0.06279232,"domain_scores_codex":[0.9893033,0.001707304,0.001768395,0.0006400547,0.00497562,0.001605318],"domain_scores_gemma":[0.9899874,0.0009262401,0.0005104736,0.0003838215,0.006858652,0.001333384],"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":[0.004445462,0.001572185,0.08856274,0.000338244,0.0002780823,0.00004964567,0.117498,0.7292241,0.0001161926,0.0125956,0.04166494,0.003654754],"study_design_scores_gemma":[0.01204636,0.003147076,0.5337585,0.001087843,0.000468741,0.000001373906,0.1173113,0.01652781,0.0001851258,0.004637551,0.3093692,0.001459124],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6138486,0.0002436961,0.3721025,0.005333511,0.00120303,0.004904646,0.0003101361,0.0001423804,0.001911553],"genre_scores_gemma":[0.9738418,0.0002723325,0.02271886,0.0001177495,0.0004382656,0.0004071018,0.0001881967,0.00008978214,0.001925947],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7126963,"threshold_uncertainty_score":0.9999614,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1203028024472339,"score_gpt":0.3881356518612334,"score_spread":0.2678328494139995,"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."}}