{"id":"W4406872735","doi":"10.1016/j.rineng.2025.104094","title":"Traffic flow modelling of vehicles on a six lane freeway: Comparative analysis of improved group method of data handling and artificial neural network model","year":2025,"lang":"en","type":"article","venue":"Results in Engineering","topic":"Traffic control and management","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Ontario Ministry of Transportation","keywords":"Artificial neural network; Traffic flow (computer networking); Computer science; Artificial intelligence; Data mining; Transport engineering; Engineering; Computer network","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004596581,0.0001589635,0.0005939899,0.0004250093,0.00001425488,0.000009051282,0.0002020613,0.00005994786,3.234363e-7],"category_scores_gemma":[0.00002307139,0.0001500055,0.00006512794,0.0007144985,0.00001590127,0.00007963669,0.00007733332,0.0001490398,3.066624e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002145686,"about_ca_system_score_gemma":0.000007226839,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004720534,"about_ca_topic_score_gemma":0.0002338125,"domain_scores_codex":[0.9988225,0.00002095608,0.0006040841,0.0002436523,0.0001118092,0.0001969938],"domain_scores_gemma":[0.9992224,0.0003003981,0.00006957712,0.000357062,0.00002345309,0.00002711856],"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":[0.000141859,0.0000331567,0.000004260849,0.0002175286,0.0005303142,7.982802e-7,0.0004844455,0.9716182,0.005762652,0.0003994026,0.000007132434,0.0208002],"study_design_scores_gemma":[0.0006200224,0.00002702385,0.0001808821,0.0001642239,0.000290996,7.457014e-8,0.00006491898,0.9979337,0.0005768487,0.00001827327,0.00001082847,0.0001122048],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2860715,0.0004426957,0.712981,0.00001117319,0.00007643327,0.00015829,0.0001312855,0.00006004866,0.00006755972],"genre_scores_gemma":[0.9343604,0.00005396347,0.06548836,0.000001870964,0.0000211387,0.000005875517,0.00005510342,0.000009765931,0.000003497753],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6482889,"threshold_uncertainty_score":0.6117045,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03977275906289343,"score_gpt":0.2669707398486086,"score_spread":0.2271979807857152,"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."}}