{"id":"W3016459259","doi":"10.3390/s20082276","title":"Determining the Optimal Restricted Driving Zone Using Genetic Algorithm in a Smart City","year":2020,"lang":"en","type":"article","venue":"Sensors","topic":"Transportation Planning and Optimization","field":"Social Sciences","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University; Laurentian University","funders":"","keywords":"Metropolitan area; Traffic congestion; Genetic algorithm; Computer science; Control (management); Transport engineering; Engineering; Geography; Artificial intelligence; Machine learning","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001276059,0.00005993369,0.00007798061,0.00003924772,0.0002826075,0.00004993366,0.00009393018,0.00005205566,0.00002202904],"category_scores_gemma":[0.0001688712,0.00005423589,0.00002432154,0.0004787798,0.00006819912,0.00006517589,0.000006660155,0.0001124514,0.000003667999],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002914983,"about_ca_system_score_gemma":0.00006782346,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000900987,"about_ca_topic_score_gemma":0.000315223,"domain_scores_codex":[0.9991984,0.000131417,0.0001553566,0.000141999,0.0001927026,0.0001800973],"domain_scores_gemma":[0.9996841,0.00009630361,0.00005841095,0.00005223202,0.00004276873,0.00006618899],"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":[0.000008173826,0.00001777721,0.4143229,0.000003547484,0.000007960353,0.00003428069,0.04681895,0.524235,0.00004545371,0.0000354795,0.00003738329,0.01443306],"study_design_scores_gemma":[0.0002364543,0.00001611177,0.4708793,0.00001828027,0.00001253319,4.854168e-7,0.003272947,0.5244133,0.00001966424,0.000004879456,0.001018611,0.0001073975],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9780347,0.00001014243,0.0207982,0.000582431,0.00007560548,0.0001108105,0.000003143432,0.00006205112,0.0003229218],"genre_scores_gemma":[0.9569676,0.00001299927,0.04272477,0.0001333946,0.00009990451,0.000001452383,0.000005332025,0.000007363572,0.00004719488],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05655639,"threshold_uncertainty_score":0.2211675,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0388142523148477,"score_gpt":0.2883093116506178,"score_spread":0.2494950593357701,"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."}}