{"id":"W4392231972","doi":"10.18280/ijsdp.190236","title":"Implementing AI-Driven Traffic Signal Systems for Enhanced Traffic Management in Dammam","year":2024,"lang":"en","type":"article","venue":"International Journal of Sustainable Development and Planning","topic":"Traffic Prediction and Management Techniques","field":"Engineering","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Traffic signal; Transport engineering; Computer science; Engineering; Real-time computing","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"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":[0.0005663537,0.0001296015,0.0001475386,0.0008283312,0.00005514634,0.0002624865,0.0001751428,0.00004099957,0.000006196758],"category_scores_gemma":[0.000006073555,0.0001281702,0.00004304629,0.0001400398,0.000009295381,0.0003752355,0.00004683571,0.0001530531,8.196712e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002467226,"about_ca_system_score_gemma":0.00004266752,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":8.681906e-7,"about_ca_topic_score_gemma":0.000001329409,"domain_scores_codex":[0.998826,0.00001036821,0.0004933046,0.0001206028,0.000250724,0.0002989898],"domain_scores_gemma":[0.9996918,0.00004833212,0.00005789227,0.00003023864,0.0001253404,0.00004633934],"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":[0.0001047212,0.00004523548,0.00008066637,0.001217923,0.001061003,0.002549723,0.008734733,0.7402937,0.0002107609,0.008832961,0.01876046,0.2181081],"study_design_scores_gemma":[0.00143676,0.00007572734,0.0007847402,0.001446519,0.00005734723,0.00008748872,0.03403529,0.5260688,0.0007786773,0.00007811443,0.4347549,0.0003955782],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7254723,0.002708325,0.2676359,0.0001201411,0.001288082,0.000480446,0.000004002075,0.0005413896,0.001749437],"genre_scores_gemma":[0.9961931,0.0002473906,0.00298246,0.00002296583,0.00016784,0.00005010163,0.00001705671,0.00001939437,0.0002997532],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4159945,"threshold_uncertainty_score":0.5226629,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00974632231136035,"score_gpt":0.2581102264967245,"score_spread":0.2483639041853642,"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."}}